Model: "unet" ┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┓ ┃ Layer (type) ┃ Output Shape ┃ Param # ┃ Connected to ┃ ┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━┩ │ input_layer │ (None, 128, 128, │ 0 │ - │ │ (InputLayer) │ 3) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d (Conv2D) │ (None, 128, 128, │ 1,792 │ input_layer[0][0] │ │ │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalization │ (None, 128, 128, │ 256 │ conv2d[0][0] │ │ (BatchNormalizatio… │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu │ (None, 128, 128, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_1 (Conv2D) │ (None, 128, 128, │ 36,928 │ leaky_re_lu[0][0] │ │ │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 128, 128, │ 256 │ conv2d_1[0][0] │ │ (BatchNormalizatio… │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_1 │ (None, 128, 128, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ max_pooling2d │ (None, 64, 64, │ 0 │ leaky_re_lu_1[0]… │ │ (MaxPooling2D) │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_2 (Conv2D) │ (None, 64, 64, │ 73,856 │ max_pooling2d[0]… │ │ │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 64, 64, │ 512 │ conv2d_2[0][0] │ │ (BatchNormalizatio… │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_2 │ (None, 64, 64, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_3 (Conv2D) │ (None, 64, 64, │ 147,584 │ leaky_re_lu_2[0]… │ │ │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 64, 64, │ 512 │ conv2d_3[0][0] │ │ (BatchNormalizatio… │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_3 │ (None, 64, 64, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ max_pooling2d_1 │ (None, 32, 32, │ 0 │ leaky_re_lu_3[0]… │ │ (MaxPooling2D) │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_4 (Conv2D) │ (None, 32, 32, │ 295,168 │ max_pooling2d_1[… │ │ │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 32, 32, │ 1,024 │ conv2d_4[0][0] │ │ (BatchNormalizatio… │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_4 │ (None, 32, 32, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_5 (Conv2D) │ (None, 32, 32, │ 590,080 │ leaky_re_lu_4[0]… │ │ │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 32, 32, │ 1,024 │ conv2d_5[0][0] │ │ (BatchNormalizatio… │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_5 │ (None, 32, 32, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ max_pooling2d_2 │ (None, 16, 16, │ 0 │ leaky_re_lu_5[0]… │ │ (MaxPooling2D) │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_6 (Conv2D) │ (None, 16, 16, │ 1,180,160 │ max_pooling2d_2[… │ │ │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 16, 16, │ 2,048 │ conv2d_6[0][0] │ │ (BatchNormalizatio… │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_6 │ (None, 16, 16, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_7 (Conv2D) │ (None, 16, 16, │ 2,359,808 │ leaky_re_lu_6[0]… │ │ │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 16, 16, │ 2,048 │ conv2d_7[0][0] │ │ (BatchNormalizatio… │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_7 │ (None, 16, 16, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ max_pooling2d_3 │ (None, 8, 8, 512) │ 0 │ leaky_re_lu_7[0]… │ │ (MaxPooling2D) │ │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_8 (Conv2D) │ (None, 8, 8, │ 4,719,616 │ max_pooling2d_3[… │ │ │ 1024) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 8, 8, │ 4,096 │ conv2d_8[0][0] │ │ (BatchNormalizatio… │ 1024) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_8 │ (None, 8, 8, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 1024) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_9 (Conv2D) │ (None, 8, 8, │ 9,438,208 │ leaky_re_lu_8[0]… │ │ │ 1024) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 8, 8, │ 4,096 │ conv2d_9[0][0] │ │ (BatchNormalizatio… │ 1024) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_9 │ (None, 8, 8, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 1024) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ up_sampling2d │ (None, 16, 16, │ 0 │ leaky_re_lu_9[0]… │ │ (UpSampling2D) │ 1024) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ concatenate │ (None, 16, 16, │ 0 │ up_sampling2d[0]… │ │ (Concatenate) │ 1536) │ │ leaky_re_lu_7[0]… │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_10 (Conv2D) │ (None, 16, 16, │ 7,078,400 │ concatenate[0][0] │ │ │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 16, 16, │ 2,048 │ conv2d_10[0][0] │ │ (BatchNormalizatio… │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_10 │ (None, 16, 16, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_11 (Conv2D) │ (None, 16, 16, │ 2,359,808 │ leaky_re_lu_10[0… │ │ │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 16, 16, │ 2,048 │ conv2d_11[0][0] │ │ (BatchNormalizatio… │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_11 │ (None, 16, 16, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ up_sampling2d_1 │ (None, 32, 32, │ 0 │ leaky_re_lu_11[0… │ │ (UpSampling2D) │ 512) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ concatenate_1 │ (None, 32, 32, │ 0 │ up_sampling2d_1[… │ │ (Concatenate) │ 768) │ │ leaky_re_lu_5[0]… │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_12 (Conv2D) │ (None, 32, 32, │ 1,769,728 │ concatenate_1[0]… │ │ │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 32, 32, │ 1,024 │ conv2d_12[0][0] │ │ (BatchNormalizatio… │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_12 │ (None, 32, 32, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_13 (Conv2D) │ (None, 32, 32, │ 590,080 │ leaky_re_lu_12[0… │ │ │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 32, 32, │ 1,024 │ conv2d_13[0][0] │ │ (BatchNormalizatio… │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_13 │ (None, 32, 32, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ up_sampling2d_2 │ (None, 64, 64, │ 0 │ leaky_re_lu_13[0… │ │ (UpSampling2D) │ 256) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ concatenate_2 │ (None, 64, 64, │ 0 │ up_sampling2d_2[… │ │ (Concatenate) │ 384) │ │ leaky_re_lu_3[0]… │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_14 (Conv2D) │ (None, 64, 64, │ 442,496 │ concatenate_2[0]… │ │ │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 64, 64, │ 512 │ conv2d_14[0][0] │ │ (BatchNormalizatio… │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_14 │ (None, 64, 64, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_15 (Conv2D) │ (None, 64, 64, │ 147,584 │ leaky_re_lu_14[0… │ │ │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 64, 64, │ 512 │ conv2d_15[0][0] │ │ (BatchNormalizatio… │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_15 │ (None, 64, 64, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ up_sampling2d_3 │ (None, 128, 128, │ 0 │ leaky_re_lu_15[0… │ │ (UpSampling2D) │ 128) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ concatenate_3 │ (None, 128, 128, │ 0 │ up_sampling2d_3[… │ │ (Concatenate) │ 192) │ │ leaky_re_lu_1[0]… │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_16 (Conv2D) │ (None, 128, 128, │ 110,656 │ concatenate_3[0]… │ │ │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 128, 128, │ 256 │ conv2d_16[0][0] │ │ (BatchNormalizatio… │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_16 │ (None, 128, 128, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_17 (Conv2D) │ (None, 128, 128, │ 36,928 │ leaky_re_lu_16[0… │ │ │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ batch_normalizatio… │ (None, 128, 128, │ 256 │ conv2d_17[0][0] │ │ (BatchNormalizatio… │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ leaky_re_lu_17 │ (None, 128, 128, │ 0 │ batch_normalizat… │ │ (LeakyReLU) │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ dropout (Dropout) │ (None, 128, 128, │ 0 │ leaky_re_lu_17[0… │ │ │ 64) │ │ │ ├─────────────────────┼───────────────────┼────────────┼───────────────────┤ │ conv2d_18 (Conv2D) │ (None, 128, 128, │ 130 │ dropout[0][0] │ │ │ 2) │ │ │ └─────────────────────┴───────────────────┴────────────┴───────────────────┘ Total params: 31,402,562 (119.79 MB) Trainable params: 31,390,786 (119.75 MB) Non-trainable params: 11,776 (46.00 KB) Epoch 1/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 9:49 5s/step - accuracy: 0.5353 - loss: 0.8174 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3172  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.5475 - loss: 0.8886 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3280  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.5536 - loss: 0.8922 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3302  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.5607 - loss: 0.8785 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3291  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.5707 - loss: 0.8596 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3270  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.5819 - loss: 0.8402 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3249  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.5937 - loss: 0.8211 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3229  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.6059 - loss: 0.8025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3213  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.6180 - loss: 0.7847 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3200  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.6296 - loss: 0.7679 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3191  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.6407 - loss: 0.7520 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3184  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.6512 - loss: 0.7368 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3180  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.6612 - loss: 0.7224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3179  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.6707 - loss: 0.7087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3180  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.6795 - loss: 0.6957 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3182  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.6879 - loss: 0.6832 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3186  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.6958 - loss: 0.6714 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3190  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.7033 - loss: 0.6601 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3196  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.7103 - loss: 0.6494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3202  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.7169 - loss: 0.6391 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3209  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.7232 - loss: 0.6293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3217  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.7292 - loss: 0.6199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3225  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.7348 - loss: 0.6110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3233  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.7401 - loss: 0.6024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3242  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.7452 - loss: 0.5942 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3251  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.7500 - loss: 0.5863 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3260  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.7546 - loss: 0.5787 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3269  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.7590 - loss: 0.5714 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3279  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.7631 - loss: 0.5644 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3288  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.7671 - loss: 0.5576 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3298  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.7710 - loss: 0.5510 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3307  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.7746 - loss: 0.5447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3317  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.7782 - loss: 0.5386 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3326  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.7815 - loss: 0.5327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3336  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.7848 - loss: 0.5270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3345  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.7879 - loss: 0.5215 - mean_absolute_error: 0.5000 - 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━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.8090 - loss: 0.4831 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3428  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.8113 - loss: 0.4788 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3437  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.8135 - loss: 0.4747 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3445  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.8156 - loss: 0.4707 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3454  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.8176 - loss: 0.4669 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3462  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.8196 - loss: 0.4631 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3470  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.8215 - loss: 0.4594 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3478  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - 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━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.8543 - loss: 0.3940 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3636  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.8554 - loss: 0.3918 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3642  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.8564 - loss: 0.3896 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3648  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.8575 - loss: 0.3875 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3654  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.8585 - loss: 0.3853 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3659  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.8594 - loss: 0.3833 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3665  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.8604 - loss: 0.3812 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3670  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - 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━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.8784 - loss: 0.3421 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3780 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.8791 - loss: 0.3406 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3784 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.8797 - loss: 0.3392 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3788 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.8803 - loss: 0.3378 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3792 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.8809 - loss: 0.3364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3796 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.8815 - loss: 0.3351 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3800 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.8821 - loss: 0.3337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3804 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.8827 - loss: 0.3324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3808 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.8833 - loss: 0.3311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3812 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.8839 - loss: 0.3298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3816 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.8844 - loss: 0.3285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3820 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.8850 - loss: 0.3273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3824 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.8855 - loss: 0.3260 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3827 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.8861 - loss: 0.3248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3831 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.8866 - loss: 0.3236 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3835 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.8871 - loss: 0.3224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3838 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.8876 - loss: 0.3212 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3842 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.8882 - loss: 0.3200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3846 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.8887 - loss: 0.3188 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3849 120/120 ━━━━━━━━━━━━━━━━━━━━ 41s 300ms/step - accuracy: 0.9486 - loss: 0.1803 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4271 - val_accuracy: 0.9616 - val_loss: 0.2518 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.3829 Epoch 2/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9712 - loss: 0.0989 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4626  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9709 - loss: 0.1000 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4633  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9711 - loss: 0.0998 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4634  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9719 - loss: 0.0979 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4637  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9724 - loss: 0.0967 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4639  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9728 - loss: 0.0957 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4641  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9732 - loss: 0.0948 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4642  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9735 - loss: 0.0940 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4644  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9738 - loss: 0.0933 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4646  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9740 - loss: 0.0928 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4648  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9741 - loss: 0.0926 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4649  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9742 - loss: 0.0923 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4650  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9742 - loss: 0.0922 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4651  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9742 - loss: 0.0921 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4651  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9743 - loss: 0.0920 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4652  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9743 - loss: 0.0919 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4653  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9744 - loss: 0.0918 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4653  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9744 - loss: 0.0916 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4654  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9744 - loss: 0.0915 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4655  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9745 - loss: 0.0913 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4655  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9746 - loss: 0.0911 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4656  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9746 - loss: 0.0910 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4656  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9746 - loss: 0.0909 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4657  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9747 - loss: 0.0908 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4657  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9747 - loss: 0.0907 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4658  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9747 - loss: 0.0906 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4658  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9747 - loss: 0.0905 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4659  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9747 - loss: 0.0904 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4659  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9747 - loss: 0.0903 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4660  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9747 - loss: 0.0903 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4660  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9748 - loss: 0.0902 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4661  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9748 - loss: 0.0901 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4661  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9748 - loss: 0.0899 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4662  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9748 - loss: 0.0898 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4662  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9748 - loss: 0.0898 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4662  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9749 - loss: 0.0897 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4663  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9749 - loss: 0.0896 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4663  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9749 - loss: 0.0896 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4664  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9749 - loss: 0.0895 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4664  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9749 - loss: 0.0894 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4664  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9749 - loss: 0.0893 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4665  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9749 - loss: 0.0893 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4665  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9749 - loss: 0.0892 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4665  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9750 - loss: 0.0891 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4666  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9750 - loss: 0.0890 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4666  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9750 - loss: 0.0890 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4667  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9750 - loss: 0.0889 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4667  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9750 - loss: 0.0888 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4667  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9750 - loss: 0.0888 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4668  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9750 - loss: 0.0887 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4668  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9750 - loss: 0.0886 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4668  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9751 - loss: 0.0886 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4669  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9751 - loss: 0.0885 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4669  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9751 - loss: 0.0884 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4670  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9751 - loss: 0.0884 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4670  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9751 - loss: 0.0883 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4670  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9751 - loss: 0.0882 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4671  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9751 - loss: 0.0882 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4671  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9751 - loss: 0.0881 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4671  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9751 - loss: 0.0880 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4672  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9752 - loss: 0.0880 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4672  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9752 - loss: 0.0879 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4672  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9752 - loss: 0.0879 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4673  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9752 - loss: 0.0878 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4673  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9752 - loss: 0.0877 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4673  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9752 - loss: 0.0877 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4674  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9752 - loss: 0.0876 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4674  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9752 - loss: 0.0876 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4674  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9752 - loss: 0.0875 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4675  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9752 - loss: 0.0874 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4675  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9752 - loss: 0.0874 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4675  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9753 - loss: 0.0873 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4676  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9753 - loss: 0.0873 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4676  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9753 - loss: 0.0872 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4676  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9753 - loss: 0.0872 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4677  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9753 - loss: 0.0871 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4677  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9753 - loss: 0.0870 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4677  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9753 - loss: 0.0870 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4678  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9753 - loss: 0.0869 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4678  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9753 - loss: 0.0869 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4678  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9753 - loss: 0.0868 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4678  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9753 - loss: 0.0868 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4679  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9753 - loss: 0.0867 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4679  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9754 - loss: 0.0867 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4679  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9754 - loss: 0.0866 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4680  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9754 - loss: 0.0866 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4680  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9754 - loss: 0.0865 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4680   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9754 - loss: 0.0865 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4680  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9754 - loss: 0.0864 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4681  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9754 - loss: 0.0864 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4681  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9754 - loss: 0.0863 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4681  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9754 - loss: 0.0863 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4682  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9754 - loss: 0.0862 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4682  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9754 - loss: 0.0862 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4682  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9754 - loss: 0.0861 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4682  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9754 - loss: 0.0861 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4683  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9755 - loss: 0.0860 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4683  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9755 - loss: 0.0860 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4683  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9755 - loss: 0.0859 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4684 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9755 - loss: 0.0859 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4684 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9755 - loss: 0.0859 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4684 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9755 - loss: 0.0858 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4684 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9755 - loss: 0.0858 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4685 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9755 - loss: 0.0857 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4685 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9755 - loss: 0.0857 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4685 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9755 - loss: 0.0856 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4685 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9755 - loss: 0.0856 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4686 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9755 - loss: 0.0855 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4686 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9755 - loss: 0.0855 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4686 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9755 - loss: 0.0855 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4686 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9755 - loss: 0.0854 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4687 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9756 - loss: 0.0854 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4687 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9756 - loss: 0.0853 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4687 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9756 - loss: 0.0853 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4687 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9756 - loss: 0.0852 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4688 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9756 - loss: 0.0852 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4688 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9756 - loss: 0.0852 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4688 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9756 - loss: 0.0851 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4688 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9756 - loss: 0.0851 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4689 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9756 - loss: 0.0850 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4689 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9764 - loss: 0.0800 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4718 - val_accuracy: 0.9606 - val_loss: 0.1757 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4889 Epoch 3/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 0.9729 - loss: 0.0822 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 290ms/step - accuracy: 0.9728 - loss: 0.0836 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4742  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 0.9731 - loss: 0.0834 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4746  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 291ms/step - accuracy: 0.9738 - loss: 0.0816 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4750  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9744 - loss: 0.0803 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4753  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9748 - loss: 0.0792 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4755  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9751 - loss: 0.0783 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4756  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9754 - loss: 0.0775 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4756  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9757 - loss: 0.0767 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4757  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9759 - loss: 0.0762 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4758  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9761 - loss: 0.0758 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4759  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9762 - loss: 0.0755 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4759  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9763 - loss: 0.0753 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4759  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9763 - loss: 0.0752 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4760  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9764 - loss: 0.0751 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4760  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9764 - loss: 0.0750 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4760  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9764 - loss: 0.0748 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4760  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9765 - loss: 0.0747 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4761  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9765 - loss: 0.0746 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4761  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9766 - loss: 0.0744 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4761  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9766 - loss: 0.0743 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4761  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9767 - loss: 0.0741 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4761  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9767 - loss: 0.0740 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4761  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9767 - loss: 0.0740 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4761  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9768 - loss: 0.0739 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4762  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9768 - loss: 0.0738 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4762  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9768 - loss: 0.0738 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4762  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9768 - loss: 0.0737 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4762  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9768 - loss: 0.0737 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4762  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9769 - loss: 0.0736 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4762  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9769 - loss: 0.0736 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4762  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9769 - loss: 0.0735 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4762  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9769 - loss: 0.0734 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4763  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9770 - loss: 0.0733 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4763  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9770 - loss: 0.0733 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4763  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9770 - loss: 0.0732 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4763  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9770 - loss: 0.0732 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4763  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9770 - loss: 0.0731 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4763  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9770 - loss: 0.0731 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4763  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9770 - loss: 0.0730 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4763  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9771 - loss: 0.0730 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4764  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9771 - loss: 0.0729 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4764  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9771 - loss: 0.0729 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4764  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9771 - loss: 0.0728 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4764  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9771 - loss: 0.0728 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4764  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9771 - loss: 0.0727 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4764  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9772 - loss: 0.0727 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4764  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9772 - loss: 0.0726 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9772 - loss: 0.0726 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9772 - loss: 0.0726 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9772 - loss: 0.0725 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9772 - loss: 0.0725 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9772 - loss: 0.0724 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9772 - loss: 0.0724 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9772 - loss: 0.0724 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9773 - loss: 0.0723 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4765  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9773 - loss: 0.0723 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9773 - loss: 0.0722 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9773 - loss: 0.0722 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9773 - loss: 0.0721 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9773 - loss: 0.0721 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9773 - loss: 0.0721 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9773 - loss: 0.0720 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9773 - loss: 0.0720 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9773 - loss: 0.0719 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9774 - loss: 0.0719 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9774 - loss: 0.0719 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9774 - loss: 0.0718 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.9774 - loss: 0.0718 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9774 - loss: 0.0718 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9774 - loss: 0.0717 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9774 - loss: 0.0717 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9774 - loss: 0.0716 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4767  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9774 - loss: 0.0716 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9774 - loss: 0.0716 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9774 - loss: 0.0716 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9774 - loss: 0.0715 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9775 - loss: 0.0715 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9775 - loss: 0.0715 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9775 - loss: 0.0714 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9775 - loss: 0.0714 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9775 - loss: 0.0713 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4768  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9775 - loss: 0.0713 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9775 - loss: 0.0713 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9775 - loss: 0.0713 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  86/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 0.9775 - loss: 0.0712 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769   87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 0.9775 - loss: 0.0712 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 0.9775 - loss: 0.0712 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 0.9775 - loss: 0.0711 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 0.9775 - loss: 0.0711 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 0.9775 - loss: 0.0711 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 0.9776 - loss: 0.0711 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9776 - loss: 0.0710 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9776 - loss: 0.0710 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9776 - loss: 0.0710 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9776 - loss: 0.0709 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9776 - loss: 0.0709 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9776 - loss: 0.0709 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9776 - loss: 0.0709 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9776 - loss: 0.0708 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9776 - loss: 0.0708 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9776 - loss: 0.0708 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4770 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9776 - loss: 0.0707 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9776 - loss: 0.0707 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9776 - loss: 0.0707 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9776 - loss: 0.0707 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9776 - loss: 0.0706 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9776 - loss: 0.0706 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9777 - loss: 0.0706 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9777 - loss: 0.0706 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9777 - loss: 0.0705 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9777 - loss: 0.0705 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4771 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9777 - loss: 0.0705 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4772 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9777 - loss: 0.0704 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4772 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9777 - loss: 0.0704 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4772 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9777 - loss: 0.0704 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4772 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9777 - loss: 0.0704 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4772 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9777 - loss: 0.0703 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4772 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9777 - loss: 0.0703 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4772 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9777 - loss: 0.0703 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4772 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 0.9784 - loss: 0.0671 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784 - val_accuracy: 0.9612 - val_loss: 0.1462 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4875 Epoch 4/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9756 - loss: 0.0707 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4780  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9753 - loss: 0.0720 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9754 - loss: 0.0717 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9761 - loss: 0.0700 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4791  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9766 - loss: 0.0688 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4794  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9770 - loss: 0.0678 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4796  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9773 - loss: 0.0670 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4797  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9776 - loss: 0.0662 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4798  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9779 - loss: 0.0654 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4799  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9781 - loss: 0.0649 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4800  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9782 - loss: 0.0646 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4801  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9783 - loss: 0.0643 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4801  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9784 - loss: 0.0641 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4801  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9784 - loss: 0.0640 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4802  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9785 - loss: 0.0639 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4802  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9785 - loss: 0.0637 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4802  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9786 - loss: 0.0636 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4802  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9786 - loss: 0.0635 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4803  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9787 - loss: 0.0633 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4803  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9787 - loss: 0.0632 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4803  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9788 - loss: 0.0630 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4803  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9788 - loss: 0.0629 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9788 - loss: 0.0628 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9789 - loss: 0.0627 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9789 - loss: 0.0626 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9789 - loss: 0.0626 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9789 - loss: 0.0626 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9790 - loss: 0.0625 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9790 - loss: 0.0625 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9790 - loss: 0.0624 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9790 - loss: 0.0623 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9790 - loss: 0.0623 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9791 - loss: 0.0622 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9791 - loss: 0.0622 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9791 - loss: 0.0621 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9791 - loss: 0.0621 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9791 - loss: 0.0620 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9791 - loss: 0.0620 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9791 - loss: 0.0620 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9792 - loss: 0.0620 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9792 - loss: 0.0619 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9792 - loss: 0.0619 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9792 - loss: 0.0619 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9792 - loss: 0.0618 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9792 - loss: 0.0618 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9792 - loss: 0.0618 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9792 - loss: 0.0617 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9792 - loss: 0.0617 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9793 - loss: 0.0617 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9793 - loss: 0.0617 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9793 - loss: 0.0617 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9793 - loss: 0.0616 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9793 - loss: 0.0616 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9793 - loss: 0.0616 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9793 - loss: 0.0616 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9793 - loss: 0.0616 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9793 - loss: 0.0615 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9793 - loss: 0.0615 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9793 - loss: 0.0615 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9793 - loss: 0.0615 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9793 - loss: 0.0614 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9793 - loss: 0.0614 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9793 - loss: 0.0614 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9794 - loss: 0.0614 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9794 - loss: 0.0614 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9794 - loss: 0.0614 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9794 - loss: 0.0613 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9794 - loss: 0.0613 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9794 - loss: 0.0613 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9794 - loss: 0.0613 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9794 - loss: 0.0613 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9794 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9794 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9794 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9794 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9794 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9794 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9794 - loss: 0.0611 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9794 - loss: 0.0611 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9794 - loss: 0.0611 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9795 - loss: 0.0611 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9795 - loss: 0.0611 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9795 - loss: 0.0610 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9795 - loss: 0.0610 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9795 - loss: 0.0610 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9795 - loss: 0.0610 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9795 - loss: 0.0610 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9795 - loss: 0.0610 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9795 - loss: 0.0609 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9795 - loss: 0.0609 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9795 - loss: 0.0609 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9795 - loss: 0.0609 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9795 - loss: 0.0609 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9795 - loss: 0.0609 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9795 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9795 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9795 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9795 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9795 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9795 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9796 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9796 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9796 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9796 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9796 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9796 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9796 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9796 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9796 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9796 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9796 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9796 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9796 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9796 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9796 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9796 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9796 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9796 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9796 - loss: 0.0604 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9796 - loss: 0.0604 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9802 - loss: 0.0583 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 - val_accuracy: 0.9720 - val_loss: 0.0992 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4865 Epoch 5/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 0.9772 - loss: 0.0625 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9768 - loss: 0.0635 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9770 - loss: 0.0632 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9776 - loss: 0.0617 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9781 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9784 - loss: 0.0598 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4818  7/120 ━━━━━━━━━━━━━━━━━━━━ 32s 291ms/step - accuracy: 0.9787 - loss: 0.0590 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4819  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 291ms/step - accuracy: 0.9790 - loss: 0.0583 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4820  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9793 - loss: 0.0576 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4821  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9795 - loss: 0.0572 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4822  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9796 - loss: 0.0569 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4823  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9797 - loss: 0.0567 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4824  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9798 - loss: 0.0565 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4824  14/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9798 - loss: 0.0564 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4824  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9798 - loss: 0.0564 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4825  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9799 - loss: 0.0563 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4825  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9799 - loss: 0.0562 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4825  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9800 - loss: 0.0561 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4825  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9800 - loss: 0.0560 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4826  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9801 - loss: 0.0559 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4826  21/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9801 - loss: 0.0558 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4826  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9802 - loss: 0.0557 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4826  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9802 - loss: 0.0556 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4826  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9802 - loss: 0.0556 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 292ms/step - accuracy: 0.9802 - loss: 0.0555 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 292ms/step - accuracy: 0.9803 - loss: 0.0555 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 0.9803 - loss: 0.0555 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  28/120 ━━━━━━━━━━━━━━━━━━━━ 26s 292ms/step - accuracy: 0.9803 - loss: 0.0554 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 0.9803 - loss: 0.0554 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 0.9803 - loss: 0.0553 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 0.9803 - loss: 0.0553 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9804 - loss: 0.0553 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9804 - loss: 0.0552 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 292ms/step - accuracy: 0.9804 - loss: 0.0552 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 292ms/step - accuracy: 0.9804 - loss: 0.0551 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 292ms/step - accuracy: 0.9804 - loss: 0.0551 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 292ms/step - accuracy: 0.9805 - loss: 0.0550 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  38/120 ━━━━━━━━━━━━━━━━━━━━ 23s 292ms/step - accuracy: 0.9805 - loss: 0.0550 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 292ms/step - accuracy: 0.9805 - loss: 0.0550 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 292ms/step - accuracy: 0.9805 - loss: 0.0550 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 292ms/step - accuracy: 0.9805 - loss: 0.0550 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 292ms/step - accuracy: 0.9805 - loss: 0.0549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 292ms/step - accuracy: 0.9805 - loss: 0.0549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 292ms/step - accuracy: 0.9805 - loss: 0.0549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  45/120 ━━━━━━━━━━━━━━━━━━━━ 21s 292ms/step - accuracy: 0.9805 - loss: 0.0549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 292ms/step - accuracy: 0.9806 - loss: 0.0548 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 292ms/step - accuracy: 0.9806 - loss: 0.0548 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 292ms/step - accuracy: 0.9806 - loss: 0.0548 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 292ms/step - accuracy: 0.9806 - loss: 0.0548 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 292ms/step - accuracy: 0.9806 - loss: 0.0548 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 292ms/step - accuracy: 0.9806 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 292ms/step - accuracy: 0.9806 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 292ms/step - accuracy: 0.9806 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 292ms/step - accuracy: 0.9806 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  55/120 ━━━━━━━━━━━━━━━━━━━━ 18s 292ms/step - accuracy: 0.9806 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 292ms/step - accuracy: 0.9806 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 292ms/step - accuracy: 0.9806 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 292ms/step - accuracy: 0.9807 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 292ms/step - accuracy: 0.9807 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 292ms/step - accuracy: 0.9807 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 292ms/step - accuracy: 0.9807 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  62/120 ━━━━━━━━━━━━━━━━━━━━ 16s 292ms/step - accuracy: 0.9807 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 292ms/step - accuracy: 0.9807 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 292ms/step - accuracy: 0.9807 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 292ms/step - accuracy: 0.9807 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 292ms/step - accuracy: 0.9807 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 292ms/step - accuracy: 0.9807 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 292ms/step - accuracy: 0.9807 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  69/120 ━━━━━━━━━━━━━━━━━━━━ 14s 292ms/step - accuracy: 0.9807 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 292ms/step - accuracy: 0.9807 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 292ms/step - accuracy: 0.9807 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 292ms/step - accuracy: 0.9807 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 292ms/step - accuracy: 0.9807 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 292ms/step - accuracy: 0.9807 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 292ms/step - accuracy: 0.9807 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 292ms/step - accuracy: 0.9807 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 292ms/step - accuracy: 0.9807 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9808 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  79/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9808 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  86/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830   87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9808 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 293ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9808 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 103/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9808 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9809 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9809 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9809 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9809 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9809 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9809 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9809 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9809 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9809 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9809 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9809 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9809 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9809 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 0.9812 - loss: 0.0532 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 - val_accuracy: 0.9767 - val_loss: 0.0699 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4836 Epoch 6/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9774 - loss: 0.0604 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9774 - loss: 0.0611 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4819  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.9776 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4821  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9782 - loss: 0.0592 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4824  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9787 - loss: 0.0581 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9791 - loss: 0.0571 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9794 - loss: 0.0564 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9797 - loss: 0.0556 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9800 - loss: 0.0549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9802 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9803 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9805 - loss: 0.0537 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4836  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9805 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4836  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9806 - loss: 0.0533 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4837  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9806 - loss: 0.0532 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4837  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9807 - loss: 0.0531 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4837  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9808 - loss: 0.0529 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4837  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9808 - loss: 0.0528 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4838  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9808 - loss: 0.0527 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4838  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9809 - loss: 0.0525 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4838  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9810 - loss: 0.0524 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4838  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9810 - loss: 0.0523 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4839  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9810 - loss: 0.0522 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4839  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9811 - loss: 0.0521 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4839  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9811 - loss: 0.0520 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4839  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9811 - loss: 0.0520 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4839  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9811 - loss: 0.0519 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9812 - loss: 0.0519 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9812 - loss: 0.0518 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9812 - loss: 0.0517 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9812 - loss: 0.0517 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9812 - loss: 0.0516 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9813 - loss: 0.0515 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9813 - loss: 0.0515 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9813 - loss: 0.0514 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9813 - loss: 0.0514 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9814 - loss: 0.0513 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9814 - loss: 0.0513 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 0.9814 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 0.9814 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 0.9814 - loss: 0.0511 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9814 - loss: 0.0511 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9814 - loss: 0.0511 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9814 - loss: 0.0510 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9815 - loss: 0.0510 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9815 - loss: 0.0509 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9815 - loss: 0.0509 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9815 - loss: 0.0508 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9815 - loss: 0.0508 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9815 - loss: 0.0508 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9815 - loss: 0.0508 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9815 - loss: 0.0507 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9815 - loss: 0.0507 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9816 - loss: 0.0507 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9816 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9816 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9816 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9816 - loss: 0.0505 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9816 - loss: 0.0505 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9816 - loss: 0.0505 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9816 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9816 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9816 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9817 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9817 - loss: 0.0503 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9817 - loss: 0.0503 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9817 - loss: 0.0503 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9817 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9817 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9817 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9817 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9817 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9817 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9817 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9817 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9817 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9817 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9818 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9818 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9818 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9818 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9818 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9818 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9818 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9818 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9818 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9818 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9818 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9818 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9818 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9818 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9818 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9818 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9818 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9818 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9819 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9819 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9819 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9819 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9819 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9819 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9819 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9819 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9819 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9819 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9819 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9819 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9819 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9819 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9819 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9819 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9819 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9819 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9819 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9819 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9819 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9819 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9819 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9819 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9819 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 0.9824 - loss: 0.0475 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851 - val_accuracy: 0.9771 - val_loss: 0.0757 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4904 Epoch 7/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9798 - loss: 0.0524 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9794 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4837  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9796 - loss: 0.0530 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4838  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9801 - loss: 0.0517 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9805 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9808 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9811 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9813 - loss: 0.0486 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9815 - loss: 0.0481 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9817 - loss: 0.0477 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9818 - loss: 0.0474 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4852  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9819 - loss: 0.0472 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9819 - loss: 0.0470 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9820 - loss: 0.0469 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9820 - loss: 0.0468 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9820 - loss: 0.0467 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9821 - loss: 0.0466 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9821 - loss: 0.0465 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9821 - loss: 0.0464 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9822 - loss: 0.0463 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9822 - loss: 0.0462 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9822 - loss: 0.0461 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9823 - loss: 0.0460 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9823 - loss: 0.0459 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9823 - loss: 0.0459 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9823 - loss: 0.0459 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9823 - loss: 0.0458 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9824 - loss: 0.0458 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9824 - loss: 0.0457 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9824 - loss: 0.0457 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9824 - loss: 0.0457 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9824 - loss: 0.0456 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9824 - loss: 0.0456 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9824 - loss: 0.0456 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9824 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9826 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9826 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9826 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9826 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9826 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9826 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9826 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9826 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 0.9833 - loss: 0.0432 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4864 - val_accuracy: 0.9779 - val_loss: 0.0709 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4898 Epoch 8/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.9816 - loss: 0.0460 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9811 - loss: 0.0466 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9812 - loss: 0.0462 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9817 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9821 - loss: 0.0441 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4864  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9824 - loss: 0.0435 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4865  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9826 - loss: 0.0430 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4867  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9828 - loss: 0.0425 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4868  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9830 - loss: 0.0421 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4869  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9832 - loss: 0.0417 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4869  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9833 - loss: 0.0415 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4870  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9834 - loss: 0.0413 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4870  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9834 - loss: 0.0412 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4870  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9835 - loss: 0.0411 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4871  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9835 - loss: 0.0410 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4871  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9836 - loss: 0.0409 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4871  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9836 - loss: 0.0408 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4871  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9836 - loss: 0.0408 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4871  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9837 - loss: 0.0407 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4871  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9837 - loss: 0.0406 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4871  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9838 - loss: 0.0405 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9838 - loss: 0.0404 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9838 - loss: 0.0403 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9839 - loss: 0.0402 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9839 - loss: 0.0402 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9839 - loss: 0.0402 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9839 - loss: 0.0401 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9840 - loss: 0.0401 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9840 - loss: 0.0400 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9840 - loss: 0.0400 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9840 - loss: 0.0400 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9840 - loss: 0.0399 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9841 - loss: 0.0399 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9841 - loss: 0.0398 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9841 - loss: 0.0398 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9841 - loss: 0.0397 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9841 - loss: 0.0397 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9841 - loss: 0.0397 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9841 - loss: 0.0397 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9841 - loss: 0.0396 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9842 - loss: 0.0396 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9842 - loss: 0.0396 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9842 - loss: 0.0396 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9842 - loss: 0.0395 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9842 - loss: 0.0395 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9842 - loss: 0.0395 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9842 - loss: 0.0394 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9842 - loss: 0.0394 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9842 - loss: 0.0394 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9842 - loss: 0.0394 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9842 - loss: 0.0394 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9843 - loss: 0.0393 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9843 - loss: 0.0393 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9843 - loss: 0.0393 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9843 - loss: 0.0393 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9843 - loss: 0.0393 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9843 - loss: 0.0392 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9843 - loss: 0.0392 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9843 - loss: 0.0392 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9843 - loss: 0.0392 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9843 - loss: 0.0392 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9843 - loss: 0.0392 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9843 - loss: 0.0391 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9843 - loss: 0.0391 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9843 - loss: 0.0391 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9843 - loss: 0.0391 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9844 - loss: 0.0391 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9844 - loss: 0.0391 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9844 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9844 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9844 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9845 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9845 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9845 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9845 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9845 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9845 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9845 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9848 - loss: 0.0379 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4878 - val_accuracy: 0.9773 - val_loss: 0.0770 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4903 Epoch 9/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9831 - loss: 0.0417 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4864  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9827 - loss: 0.0422 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4864  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9827 - loss: 0.0421 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4866  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9831 - loss: 0.0412 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4869  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9834 - loss: 0.0404 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9837 - loss: 0.0399 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9839 - loss: 0.0394 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9840 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9842 - loss: 0.0386 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4878  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9843 - loss: 0.0383 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4879  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9844 - loss: 0.0381 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4879  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9845 - loss: 0.0379 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9846 - loss: 0.0377 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9846 - loss: 0.0377 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9846 - loss: 0.0376 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9847 - loss: 0.0375 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9847 - loss: 0.0375 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9847 - loss: 0.0374 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9848 - loss: 0.0373 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9848 - loss: 0.0372 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9848 - loss: 0.0371 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9849 - loss: 0.0370 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9849 - loss: 0.0370 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9849 - loss: 0.0369 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9850 - loss: 0.0368 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9850 - loss: 0.0368 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9850 - loss: 0.0368 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9850 - loss: 0.0367 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9850 - loss: 0.0367 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9850 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9851 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9851 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9851 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9851 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9852 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9852 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9852 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9852 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9853 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9853 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9853 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9853 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9853 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9853 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9853 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9854 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9854 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9854 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9854 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9854 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9854 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9854 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9854 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9854 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9854 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9854 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9854 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9854 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9854 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9854 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9854 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9855 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9855 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9855 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9855 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9855 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9855 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9855 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9855 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9855 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9855 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9855 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9856 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9856 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9856 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9856 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9856 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9856 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9856 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9856 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9859 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890 - val_accuracy: 0.9761 - val_loss: 0.0742 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4889 Epoch 10/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9836 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4878  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9834 - loss: 0.0393 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9835 - loss: 0.0390 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9839 - loss: 0.0382 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4877  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9842 - loss: 0.0375 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4878  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9845 - loss: 0.0370 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9846 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9848 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9850 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9851 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9852 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9853 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9853 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9854 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9854 - loss: 0.0351 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9854 - loss: 0.0351 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9854 - loss: 0.0350 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9855 - loss: 0.0350 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9855 - loss: 0.0349 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9855 - loss: 0.0349 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9856 - loss: 0.0348 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9856 - loss: 0.0347 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9856 - loss: 0.0347 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9856 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9856 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9857 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9857 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9857 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9857 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9857 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9857 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9857 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9857 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9857 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9858 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9858 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9858 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9858 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9858 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9858 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9858 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9859 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9859 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9859 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9859 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9859 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9859 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9859 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9860 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9860 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9860 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9860 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9861 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9861 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9861 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9861 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9861 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9861 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9861 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9861 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9861 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9861 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9861 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9861 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9861 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9862 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9862 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9862 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9862 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9862 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9862 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9862 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9862 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9862 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9862 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9862 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9862 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9862 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9862 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9862 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9862 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9863 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9863 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9863 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9863 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9863 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9863 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9863 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9863 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9863 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9863 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9863 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9863 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9863 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9863 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9863 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9863 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9863 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9869 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898 - val_accuracy: 0.9765 - val_loss: 0.0787 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4908 Epoch 11/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 0.9842 - loss: 0.0371 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9841 - loss: 0.0370 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9844 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9849 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9853 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9855 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9857 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9860 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9862 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9863 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9864 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9865 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9866 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9866 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9867 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9867 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9868 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9868 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9869 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9870 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9870 - loss: 0.0309 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9871 - loss: 0.0308 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9871 - loss: 0.0307 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9871 - loss: 0.0306 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9872 - loss: 0.0306 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9872 - loss: 0.0305 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9872 - loss: 0.0305 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9872 - loss: 0.0304 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9873 - loss: 0.0304 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9873 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9873 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9873 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9874 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9874 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9874 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9874 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9874 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9875 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9875 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9875 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9875 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9875 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9875 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9875 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9876 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9876 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9876 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9880 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 0.9883 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909 - val_accuracy: 0.9753 - val_loss: 0.0833 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4904 Epoch 12/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9859 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 0.9856 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9858 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9862 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9865 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9866 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9868 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9870 - loss: 0.0308 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9871 - loss: 0.0304 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9873 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9875 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9875 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9876 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9880 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9880 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9880 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9880 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9880 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9880 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9880 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9880 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9881 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9882 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9882 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9883 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 - val_accuracy: 0.9751 - val_loss: 0.0965 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4923 Epoch 13/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9857 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9854 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9856 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9860 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9863 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9866 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9867 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9869 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9871 - loss: 0.0307 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9872 - loss: 0.0305 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9873 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9874 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9874 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9875 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9875 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9879 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9880 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9880 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9880 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9881 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9881 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9881 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9882 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9882 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9883 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9884 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9885 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9885 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914 - val_accuracy: 0.9751 - val_loss: 0.0878 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4909 Epoch 14/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9858 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9856 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9859 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9864 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9867 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9870 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9872 - loss: 0.0306 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9873 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9875 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9878 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9879 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9880 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9880 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9881 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9881 - loss: 0.0285 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9882 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9882 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9882 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9882 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9883 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9883 - loss: 0.0282 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9883 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9883 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9884 - loss: 0.0280 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9884 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9884 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9885 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9885 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9885 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9885 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9886 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9886 - loss: 0.0274 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9886 - loss: 0.0274 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9886 - loss: 0.0274 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9886 - loss: 0.0274 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9886 - loss: 0.0274 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9886 - loss: 0.0274 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9886 - loss: 0.0274 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9886 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9886 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9886 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9886 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9887 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9887 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9887 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9887 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9887 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9887 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9887 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9887 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9887 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9887 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9887 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9887 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9887 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9888 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9888 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9888 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9888 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9888 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9888 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9888 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9888 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9888 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9888 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9888 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9888 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9888 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9888 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9888 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9888 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9888 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9888 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9888 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9889 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9889 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9889 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9889 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9889 - loss: 0.0267 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9889 - loss: 0.0267 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9889 - loss: 0.0267 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9889 - loss: 0.0267 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9895 - loss: 0.0252 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920 - val_accuracy: 0.9758 - val_loss: 0.0905 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4922 Epoch 15/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9893 - loss: 0.0251 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9891 - loss: 0.0256 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9893 - loss: 0.0254 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9896 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9898 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9899 - loss: 0.0240 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9900 - loss: 0.0238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9902 - loss: 0.0235 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9903 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9903 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9904 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9904 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9904 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9904 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9906 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9906 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9905 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9905 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9905 - loss: 0.0230 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9904 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9904 - loss: 0.0232 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9904 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9903 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9903 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9903 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9903 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9903 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9903 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9903 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9901 - loss: 0.0239 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 - val_accuracy: 0.9760 - val_loss: 0.1122 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4945 Epoch 16/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 0.9884 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 0.9882 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 0.9883 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9887 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9889 - loss: 0.0263 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9890 - loss: 0.0260 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9891 - loss: 0.0258 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9892 - loss: 0.0257 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9893 - loss: 0.0254 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9894 - loss: 0.0253 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9894 - loss: 0.0252 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9895 - loss: 0.0251 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9895 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9895 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9895 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9895 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9895 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9896 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9896 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9896 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9896 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9896 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9896 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9897 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9897 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9897 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9897 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9897 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9897 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9897 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9897 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9898 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9898 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9898 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9898 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9898 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9898 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9898 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9898 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9898 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9898 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9898 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9898 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9898 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9899 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9899 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9899 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9899 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9899 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9899 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9899 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9899 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9899 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9899 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9899 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9899 - loss: 0.0242 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9899 - loss: 0.0242 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9899 - loss: 0.0242 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9899 - loss: 0.0242 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9899 - loss: 0.0242 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9900 - loss: 0.0242 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9900 - loss: 0.0241 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9900 - loss: 0.0241 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9900 - loss: 0.0241 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9900 - loss: 0.0241 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9900 - loss: 0.0241 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9900 - loss: 0.0241 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9900 - loss: 0.0240 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9900 - loss: 0.0240 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9900 - loss: 0.0240 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9900 - loss: 0.0240 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9900 - loss: 0.0240 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9900 - loss: 0.0239 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9901 - loss: 0.0239 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9901 - loss: 0.0239 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9901 - loss: 0.0239 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9901 - loss: 0.0239 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9901 - loss: 0.0238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9901 - loss: 0.0238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9901 - loss: 0.0238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9901 - loss: 0.0238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9901 - loss: 0.0238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9901 - loss: 0.0237 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9901 - loss: 0.0237 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9902 - loss: 0.0237 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9902 - loss: 0.0237 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9902 - loss: 0.0236 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9902 - loss: 0.0236 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9902 - loss: 0.0236 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9902 - loss: 0.0236 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9902 - loss: 0.0236 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9902 - loss: 0.0235 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9902 - loss: 0.0235 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9902 - loss: 0.0235 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9902 - loss: 0.0235 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9903 - loss: 0.0235 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9903 - loss: 0.0234 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9914 - loss: 0.0208 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4933 - val_accuracy: 0.9766 - val_loss: 0.1012 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4945 Epoch 17/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9912 - loss: 0.0206 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4938  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9912 - loss: 0.0206 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9915 - loss: 0.0201 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9918 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4939  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9921 - loss: 0.0189 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4940  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9922 - loss: 0.0186 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9923 - loss: 0.0184 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9924 - loss: 0.0182 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9925 - loss: 0.0181 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9925 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9926 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9926 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9926 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9926 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9926 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9926 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9927 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9927 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9926 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9926 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9926 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9926 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9926 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9926 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9927 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9927 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9928 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9928 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9928 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9928 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9928 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9928 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9928 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9928 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9928 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9928 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9928 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9929 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9929 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9929 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9929 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9929 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9929 - loss: 0.0174 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9929 - loss: 0.0174 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946 - val_accuracy: 0.9756 - val_loss: 0.1060 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4941 Epoch 18/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9925 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9925 - loss: 0.0183 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9925 - loss: 0.0183 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9927 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9928 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9929 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9930 - loss: 0.0173 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9930 - loss: 0.0171 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9931 - loss: 0.0170 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9932 - loss: 0.0169 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9932 - loss: 0.0168 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9932 - loss: 0.0168 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9932 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9932 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9932 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9933 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9933 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9935 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9934 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9934 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9933 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9933 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9933 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9933 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9933 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9932 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9932 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9932 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9930 - loss: 0.0172 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945 - val_accuracy: 0.9764 - val_loss: 0.1163 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4952 Epoch 19/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9942 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9937 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9937 - loss: 0.0155 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9938 - loss: 0.0153 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9939 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9944 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9944 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9944 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 - val_accuracy: 0.9760 - val_loss: 0.1242 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4954 Epoch 20/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9933 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9931 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9932 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9933 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9934 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9936 - loss: 0.0154 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9937 - loss: 0.0152 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9938 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9938 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9938 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9938 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9940 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9940 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9940 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9940 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9940 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9941 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9943 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9943 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9943 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9943 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9950 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 - val_accuracy: 0.9768 - val_loss: 0.1225 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4959 Epoch 21/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4963  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9960 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4962  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4962  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9962 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4963  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9961 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4963  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9961 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4963  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9961 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9960 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9960 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9960 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9960 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9960 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9960 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9960 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9959 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9959 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9959 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9959 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9959 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9959 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9959 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9959 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9958 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9958 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9958 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9958 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9958 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9958 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9958 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9958 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9958 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9958 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9958 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9958 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9957 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9957 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9957 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9957 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9957 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9957 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9957 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9957 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9957 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9957 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9957 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9957 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9957 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9957 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9957 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9957 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9956 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9956 - loss: 0.0111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9959 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4966 - val_accuracy: 0.9758 - val_loss: 0.1395 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4963 Epoch 22/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9952 - loss: 0.0119 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9949 - loss: 0.0125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9949 - loss: 0.0125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4964  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9951 - loss: 0.0121 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9953 - loss: 0.0117 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9954 - loss: 0.0114 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4966  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9955 - loss: 0.0112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4966  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9956 - loss: 0.0110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9956 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9957 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9957 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9957 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9957 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9957 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9957 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9957 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9958 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9958 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9959 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9959 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9959 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9959 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9959 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9959 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9959 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9959 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4967  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9959 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9959 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9959 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9959 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9959 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9959 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9959 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9959 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9960 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9960 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9960 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9960 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9960 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9960 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9960 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9960 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9960 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9960 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9960 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9960 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9960 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9961 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9961 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9961 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9961 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9961 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9961 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9961 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9961 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9961 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9961 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9961 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9961 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9961 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9962 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9962 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9962 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9962 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9962 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9962 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9962 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9962 - loss: 0.0096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9962 - loss: 0.0096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9962 - loss: 0.0096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9962 - loss: 0.0096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9962 - loss: 0.0096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9962 - loss: 0.0096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9963 - loss: 0.0095 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9963 - loss: 0.0095 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9963 - loss: 0.0095 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9963 - loss: 0.0095 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9963 - loss: 0.0095 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9963 - loss: 0.0095 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9963 - loss: 0.0095 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4969 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9971 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 - val_accuracy: 0.9771 - val_loss: 0.1416 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4969 Epoch 23/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9978 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9979 - loss: 0.0058 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 - val_accuracy: 0.9757 - val_loss: 0.1531 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4966 Epoch 24/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9978 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - 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━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9979 - loss: 0.0058 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 - val_accuracy: 0.9750 - val_loss: 0.1535 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4962 Epoch 25/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9977 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9977 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9978 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9978 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9978 - loss: 0.0059 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9979 - loss: 0.0058 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9980 - loss: 0.0056 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9980 - loss: 0.0056 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9980 - loss: 0.0056 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9981 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9982 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9982 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9983 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9984 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9985 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9985 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9985 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9985 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9986 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9986 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9986 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9986 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9986 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9986 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9986 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9986 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9988 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9994 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 - val_accuracy: 0.9771 - val_loss: 0.1702 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4977 Epoch 26/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.1855e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 3.2465e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 3.2322e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 3.1600e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.1018e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.0533e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.0157e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.9810e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.9463e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.9205e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.9014e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 2.8846e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 2.8719e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 2.8630e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 2.8548e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 2.8452e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 2.8347e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 2.8248e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.8152e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.8052e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.7947e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.7853e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.7768e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.7688e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.7615e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.7553e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.7498e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.7438e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.7377e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.7316e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.7255e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.7193e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.7129e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.7068e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.7012e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 2.6956e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 2.6904e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 2.6858e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.6813e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.6766e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.6718e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.6670e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.6622e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.6574e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.6524e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.6477e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.6431e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.6385e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.6341e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.6299e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.6258e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.6216e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 2.6174e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 2.6133e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 2.6092e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.6050e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.6008e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.5966e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.5926e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.5886e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.5847e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.5810e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.5774e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.5737e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.5701e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.5664e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.5628e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.5592e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.5555e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 2.5519e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 2.5484e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 2.5448e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.5414e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.5382e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.5350e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.5317e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.5285e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.5253e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.5220e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 2.5188e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 2.5156e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 2.5123e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 2.5092e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 2.5060e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 2.5029e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 2.4999e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 2.4970e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 2.4940e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 2.4910e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 2.4881e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 2.4851e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 2.4822e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 2.4792e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 2.4762e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 2.4733e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 2.4704e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 2.4675e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 2.4648e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 2.4620e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 2.4593e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 2.4565e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 2.4538e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 2.4510e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 2.4483e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 2.4455e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 2.4428e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 2.4401e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 2.4374e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 2.4347e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 2.4322e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 2.4296e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 2.4270e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 2.4245e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 2.4219e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 2.4193e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 2.4168e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 2.4142e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 2.4116e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 2.4091e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 2.4066e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 2.1072e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 - val_accuracy: 0.9772 - val_loss: 0.1882 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4980 Epoch 27/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 1.9488e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 2.0288e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 2.0235e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.9823e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.9421e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.9106e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.8849e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.8608e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.8379e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.8205e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.8073e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.7951e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7856e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7798e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7747e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.7691e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.7632e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.7576e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.7523e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.7472e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.7416e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.7368e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.7327e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.7284e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.7247e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7218e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7191e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7161e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7130e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7100e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7072e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.7042e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.7011e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.6982e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.6955e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.6928e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.6903e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.6881e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.6860e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.6839e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.6818e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.6797e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.6776e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.6755e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.6733e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.6711e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.6691e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.6670e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.6651e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.6633e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.6617e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.6599e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.6582e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.6564e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.6546e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6528e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6510e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.6492e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.6474e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6457e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6440e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6424e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.6409e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.6393e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.6378e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.6363e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.6348e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.6332e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.6316e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6301e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6286e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6271e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6256e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6242e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6229e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6215e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6202e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6189e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6175e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6162e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6148e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6135e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6122e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6109e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6096e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6084e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6072e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6060e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6048e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6036e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6024e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6012e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6000e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.5988e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.5976e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.5964e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.5953e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.5942e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.5931e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.5920e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.5909e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.5898e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.5887e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.5876e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.5864e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.5853e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5842e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5831e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5821e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5810e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5800e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5789e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5779e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5768e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5758e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5747e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5736e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5726e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5715e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5705e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.4456e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 - val_accuracy: 0.9772 - val_loss: 0.1985 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4982 Epoch 28/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.3751e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.4070e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.4072e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3882e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.3726e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.3584e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.3479e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.3383e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3274e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3194e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3138e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3082e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3039e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3014e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2995e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2971e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2944e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2917e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2891e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2865e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2835e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2809e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2787e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2764e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2745e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2730e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2716e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2701e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2686e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2671e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2657e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2644e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2629e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2616e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2605e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2596e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2588e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2582e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2577e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.2570e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.2562e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.2554e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.2547e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.2540e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.2533e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.2527e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.2521e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.2517e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.2513e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.2510e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.2507e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.2503e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2498e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2494e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2488e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2484e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2478e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2473e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2468e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2463e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2459e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2456e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2452e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2448e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2444e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2439e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.2434e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.2430e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.2424e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2419e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2415e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2410e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2405e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2401e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2397e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2393e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2388e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2384e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2379e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2374e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2369e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2365e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2360e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2355e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2350e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2346e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2343e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.2338e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.2334e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2330e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2326e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2321e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2317e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2312e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2308e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2303e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2299e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2295e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2291e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2287e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2282e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2278e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2273e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2269e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2264e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2259e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2255e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2250e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2245e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2241e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2236e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2232e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2227e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2222e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2217e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2213e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2208e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2203e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2198e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2193e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.1594e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 - val_accuracy: 0.9772 - val_loss: 0.2059 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4983 Epoch 29/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.1290e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.1750e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.1772e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.1584e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.1384e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.1204e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.1059e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.0934e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.0811e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.0722e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.0657e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.0594e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.0549e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.0529e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.0515e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.0495e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.0479e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.0461e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.0454e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.0442e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.0427e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.0414e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.0404e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.0393e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.0385e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.0386e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.0387e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.0386e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.0382e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.0377e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.0372e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.0365e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.0357e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.0350e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.0344e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.0336e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.0330e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.0328e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.0327e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.0324e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.0321e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.0317e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.0313e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.0309e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.0303e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.0298e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.0293e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.0288e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.0283e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.0280e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.0277e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.0274e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.0269e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.0265e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.0260e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 1.0255e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 1.0250e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 1.0244e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 1.0239e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 1.0234e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 1.0229e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 1.0224e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 1.0220e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 1.0215e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 1.0210e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.0205e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.0200e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.0195e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.0189e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.0183e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.0178e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.0172e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.0167e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.0162e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.0157e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.0152e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.0146e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.0141e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.0135e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.0130e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.0124e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.0118e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.0113e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.0107e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.0101e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.0096e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.0091e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.0085e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.0080e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.0074e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.0069e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.0063e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.0057e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.0052e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.0046e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.0041e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.0035e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.0030e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.0025e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.0020e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.0015e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.0009e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.0004e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 9.9990e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 9.9936e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 9.9882e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 9.9830e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 9.9778e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 9.9727e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 9.9678e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 9.9630e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 9.9581e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 9.9532e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 9.9482e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 9.9434e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 9.9384e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 9.9334e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 9.9284e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 9.9235e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 9.9186e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 9.3322e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 - val_accuracy: 0.9771 - val_loss: 0.2110 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4983 Epoch 30/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 9.8725e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0161e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0187e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0024e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 9.8492e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 9.7100e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.6053e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 9.5166e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 9.4226e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.3484e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.2960e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.2441e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.2087e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.1930e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.1808e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.1634e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.1430e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.1224e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.1026e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.0816e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.0593e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.0394e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.0226e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.0045e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.9898e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.9799e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.9744e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.9675e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.9594e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.9512e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.9434e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.9345e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.9262e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.9181e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.9114e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.9039e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.8970e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.8916e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.8911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.8895e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.8872e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.8848e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.8822e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.8791e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.8753e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.8715e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.8682e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.8643e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.8636e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.8638e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.8654e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 8.8663e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.8665e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.8664e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.8660e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.8649e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.8634e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.8617e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.8602e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.8582e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.8622e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.8664e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.8704e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.8737e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.8765e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.8791e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.8813e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.8831e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.8843e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.8853e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.8862e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.8868e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.8884e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.8903e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.8927e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.8946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.8962e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.8975e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.8984e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.8990e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.8993e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.8995e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.8996e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.8994e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.8997e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.9001e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.9004e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.9005e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.9004e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.9000e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.8995e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.8986e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.8975e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.8964e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.8952e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.8937e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.8924e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.8911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.8898e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.8883e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.8866e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.8848e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.8828e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.8807e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.8784e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.8761e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.8738e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.8713e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.8690e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.8667e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.8646e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.8624e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.8600e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.8576e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.8551e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.8524e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.8496e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.8468e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.8440e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.8412e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 8.4986e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 - val_accuracy: 0.9771 - val_loss: 0.2149 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4984 Epoch 31/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 9.9385e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 9.7090e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 9.4314e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 9.1225e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 8.8781e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.6843e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 8.5347e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.4013e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.2770e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.1765e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 8.1009e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.0321e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 7.9783e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 7.9347e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 7.8994e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 7.8650e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 7.8310e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 7.7992e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.7709e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.7429e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 7.7151e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 7.6904e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 7.6688e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 7.6478e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 7.6296e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.6161e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.6039e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.5909e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.5777e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.5646e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.5521e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.5397e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 7.5267e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 7.5145e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 7.5034e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.4923e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.4820e-05 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.3122e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.3057e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.2994e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.2936e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.2881e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.2825e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.2769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.2713e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 7.2658e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 7.2603e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 7.2545e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 7.2490e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 7.2436e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 7.2382e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 7.2332e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 7.2287e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.2245e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.2203e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 7.2159e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 7.2115e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 7.2072e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 7.2028e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 7.1982e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 7.1939e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 7.1897e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 7.1855e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 7.1815e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 7.1777e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 7.1741e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 7.1705e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 7.1668e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 7.1631e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 7.1595e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 7.1559e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 7.1523e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.1487e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.1452e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.1416e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.1382e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.1348e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.1315e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.1282e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.1249e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.1215e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.1182e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.1148e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.1114e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.1080e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.1048e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.1014e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.0982e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.0951e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.0922e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.0891e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.0861e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.0830e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.0800e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.0769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.0737e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.0706e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.0676e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.0645e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 6.7026e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 - val_accuracy: 0.9771 - val_loss: 0.2200 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4984 Epoch 32/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 6.8552e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 7.0085e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.9892e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 6.8931e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 6.7879e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 6.7036e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 6.6503e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 6.5978e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 6.5389e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.5015e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.4744e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.4459e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.4257e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.4150e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.4090e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.3999e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 6.3897e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 6.3798e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.3712e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.3626e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.3524e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.3434e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.3365e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.3290e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.3228e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.3200e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.3197e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.3179e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.3152e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 6.3121e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 6.3090e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 6.3055e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 6.3008e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 6.2966e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 6.2931e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 6.2895e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 6.2862e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 6.2844e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 6.2827e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 6.2805e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 6.2778e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 6.2751e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.2723e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.2692e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.2656e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.2623e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.2594e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.2562e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.2532e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.2516e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.2504e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.2488e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.2470e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.2452e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.2435e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.2416e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.2393e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.2371e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.2350e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.2327e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.2306e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.2295e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.2285e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.2276e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.2265e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.2254e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.2242e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.2229e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.2214e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.2199e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.2184e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.2168e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.2153e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.2146e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.2140e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.2149e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.2157e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.2163e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.2168e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.2171e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.2172e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.2172e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.2172e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.2173e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.2173e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.2179e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.2184e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.2201e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.2215e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.2228e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.2241e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.2253e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.2262e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.2271e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.2280e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.2287e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.2294e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.2311e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.2326e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2355e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2382e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2409e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2434e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2458e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2479e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2501e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2522e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2543e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2562e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.2586e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.2609e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.2658e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.2705e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.2751e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.2795e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.2838e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.2878e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.2918e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.2957e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.2994e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 6.7457e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 - val_accuracy: 0.9771 - val_loss: 0.2237 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4985 Epoch 33/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 6.7334e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.3078e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.4413e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 9.9217e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0445e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0615e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0631e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0557e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0435e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0347e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0256e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0151e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.0047e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.9832e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.9155e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.8867e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.8476e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.8028e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.7539e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.7033e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.6489e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.6008e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.5527e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.5031e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 9.4547e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 9.4301e-05 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.8060e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.8240e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.8408e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.8564e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.8737e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.8898e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.9076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.9246e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.9410e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.9567e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.9747e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.9919e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.0009e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.0025e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.0042e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.0057e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.0073e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.0088e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.0104e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.0119e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.0134e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.0148e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.0164e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.0179e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.0195e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.0211e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.0229e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.0246e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.0263e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.0278e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.0296e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.0312e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.0329e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.0346e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.0363e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.0380e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.0396e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.0412e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.0429e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.0445e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.0461e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.0477e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.0492e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.0508e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.0525e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 1.2507e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 - val_accuracy: 0.9772 - val_loss: 0.2229 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4985 Epoch 34/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.0896e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.4248e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.5940e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.6144e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.6017e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.6081e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.5984e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.5872e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.5762e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.5722e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.5659e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.5728e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.5814e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.5897e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.6004e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.6062e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.6088e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.6105e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.6111e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.6104e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.6127e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.6176e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.6213e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.6288e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.6374e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.6451e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.6568e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.6663e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.6745e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.6820e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.6890e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.6956e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.7036e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.7127e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.7214e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.7310e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.7427e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.7535e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.7650e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.7753e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.7849e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.7940e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.8024e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.8109e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.8200e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.8289e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.8378e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.8466e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.8562e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.8654e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.8741e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.8821e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.8900e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.8977e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9052e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9130e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9221e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9312e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9401e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9485e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9569e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9655e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9738e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9817e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9897e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9975e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.0051e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.0129e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.0210e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.0289e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.0369e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.0450e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.0540e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.0630e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.0718e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.0803e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.0894e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.0984e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.1072e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1164e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1257e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1348e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1441e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1531e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1628e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1723e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1816e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1907e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1998e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.2090e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.2180e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.2271e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.2361e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.2454e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.2550e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.2643e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.2741e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.2839e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.2938e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.3035e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.3133e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.3231e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.3326e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.3422e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.3518e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.3614e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.3715e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.3818e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.3924e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.4032e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.4141e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.4248e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.4355e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.4464e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.4573e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.4684e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.4797e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.4911e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.5026e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.5140e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9999 - loss: 3.8756e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 - val_accuracy: 0.9769 - val_loss: 0.2080 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4982 Epoch 35/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9997 - loss: 8.4620e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9997 - loss: 9.0718e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9997 - loss: 9.1706e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9997 - loss: 9.1362e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9997 - loss: 9.0722e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9997 - loss: 9.0505e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9997 - loss: 8.9790e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9997 - loss: 8.9128e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9997 - loss: 8.8824e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9997 - loss: 8.8998e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9997 - loss: 8.9472e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9997 - loss: 8.9858e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9997 - loss: 9.0184e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9997 - loss: 9.0724e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 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━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9995 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9995 - loss: 0.0014 - 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━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 - val_accuracy: 0.9743 - val_loss: 0.1830 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4968 Epoch 36/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9968 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9967 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9967 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9968 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9968 - loss: 0.0083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9968 - loss: 0.0084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9968 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9968 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9967 - loss: 0.0085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9967 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9967 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9967 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9967 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9967 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9967 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9967 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9966 - loss: 0.0088 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9966 - loss: 0.0088 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9966 - loss: 0.0088 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9966 - loss: 0.0088 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9966 - loss: 0.0088 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9966 - loss: 0.0088 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9966 - loss: 0.0087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9967 - loss: 0.0086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975 - val_accuracy: 0.9749 - val_loss: 0.1778 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4968 Epoch 37/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9977 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9976 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9977 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 300ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 300ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 300ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 300ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 300ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 300ms/step - accuracy: 0.9975 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  13/120 ━━━━━━━━━━━━━━━━━━━━ 32s 300ms/step - accuracy: 0.9974 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 300ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 300ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 300ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 300ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 300ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  23/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 300ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 300ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 300ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  33/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9974 - loss: 0.0069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9974 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9974 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9974 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9974 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9974 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9975 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9975 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9975 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9976 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9976 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9976 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9976 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9976 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9976 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9977 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9977 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9977 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9977 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9977 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9978 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984 - val_accuracy: 0.9753 - val_loss: 0.1821 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4971 Epoch 38/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9987 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9986 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9986 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9985 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9985 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 - val_accuracy: 0.9765 - val_loss: 0.1853 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4977 Epoch 39/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9999 - loss: 5.0157e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9999 - loss: 4.7645e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9999 - loss: 4.5746e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9999 - loss: 4.4549e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9999 - loss: 4.6668e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9999 - loss: 5.0189e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9999 - loss: 5.2869e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9999 - loss: 5.4824e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9999 - loss: 5.5913e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9999 - loss: 5.6504e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9999 - loss: 5.6802e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9999 - loss: 5.6928e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9999 - loss: 5.7196e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9999 - loss: 5.7545e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9999 - loss: 5.7776e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9999 - loss: 5.7828e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9999 - loss: 5.7818e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9999 - loss: 5.7731e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9999 - loss: 5.7554e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9999 - loss: 5.7314e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9999 - loss: 5.7023e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9999 - loss: 5.6712e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9999 - loss: 5.6396e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9999 - loss: 5.6061e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9999 - loss: 5.5721e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9999 - loss: 5.5380e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9999 - loss: 5.5029e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9999 - loss: 5.4658e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9999 - loss: 5.4277e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9999 - loss: 5.3886e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9999 - loss: 5.3490e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9999 - loss: 5.3091e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9999 - loss: 5.2688e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9999 - loss: 5.2287e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9999 - loss: 5.1889e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9999 - loss: 5.1492e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9999 - loss: 5.1098e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9999 - loss: 5.0708e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9999 - loss: 5.0322e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9999 - loss: 4.9939e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9999 - loss: 4.9560e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9999 - loss: 4.9185e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9999 - loss: 4.8814e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9999 - loss: 4.8447e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9999 - loss: 4.8085e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9999 - loss: 4.7728e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9999 - loss: 4.7378e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9999 - loss: 4.7032e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9999 - loss: 4.6693e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9999 - loss: 4.6358e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9999 - loss: 4.6030e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9999 - loss: 4.5705e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9999 - loss: 4.5386e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9999 - loss: 4.5071e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9999 - loss: 4.4762e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9999 - loss: 4.4457e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9999 - loss: 4.4156e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9999 - loss: 4.3860e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9999 - loss: 4.3569e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9999 - loss: 4.3282e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9999 - loss: 4.3000e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9999 - loss: 4.2722e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9999 - loss: 4.2449e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9999 - loss: 4.2180e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9999 - loss: 4.1914e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9999 - loss: 4.1653e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9999 - loss: 4.1396e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9999 - loss: 4.1142e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9999 - loss: 4.0892e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9999 - loss: 4.0645e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9999 - loss: 4.0403e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9999 - loss: 4.0164e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9999 - loss: 3.9928e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9999 - loss: 3.9697e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9999 - loss: 3.9468e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9999 - loss: 3.9243e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9999 - loss: 3.9021e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9999 - loss: 3.8802e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9999 - loss: 3.8587e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9999 - loss: 3.8374e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9999 - loss: 3.8164e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9999 - loss: 3.7957e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9999 - loss: 3.7753e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9999 - loss: 3.7552e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9999 - loss: 3.7354e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9999 - loss: 3.7159e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9999 - loss: 3.6966e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9999 - loss: 3.6775e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9999 - loss: 3.6587e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9999 - loss: 3.6402e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9999 - loss: 3.6219e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9999 - loss: 3.6038e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9999 - loss: 3.5859e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9999 - loss: 3.5683e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9999 - loss: 3.5509e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9999 - loss: 3.5338e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9999 - loss: 3.5168e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9999 - loss: 3.5001e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9999 - loss: 3.4836e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9999 - loss: 3.4672e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9999 - loss: 3.4511e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9999 - loss: 3.4352e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9999 - loss: 3.4194e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9999 - loss: 3.4039e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9999 - loss: 3.3885e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9999 - loss: 3.3733e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9999 - loss: 3.3583e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9999 - loss: 3.3435e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9999 - loss: 3.3288e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9999 - loss: 3.3143e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9999 - loss: 3.3000e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9999 - loss: 3.2859e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9999 - loss: 3.2719e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9999 - loss: 3.2580e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9999 - loss: 3.2443e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9999 - loss: 3.2308e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9999 - loss: 3.2174e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9999 - loss: 3.2041e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9999 - loss: 3.1910e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9999 - loss: 3.1781e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.6355e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 - val_accuracy: 0.9771 - val_loss: 0.2048 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4982 Epoch 40/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 6.1227e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 6.2340e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.2049e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.0995e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.9862e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.8893e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 5.8223e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 5.7689e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 5.7115e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.6681e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.6402e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.6137e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 5.5986e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 5.5882e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 5.5800e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 5.5708e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 5.5599e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 5.5486e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 5.5372e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 5.5271e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 5.5153e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 5.5043e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 5.4952e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 5.4855e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 5.4780e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 5.4718e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 5.4661e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 5.4600e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 5.4537e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.4468e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.4399e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.4326e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.4247e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.4174e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.4106e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.4035e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.3969e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.3909e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.3849e-05 - mean_absolute_error: 0.5000 - 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mean_squared_error: 0.4999  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.3314e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.3248e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.3184e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.3123e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.3065e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.3007e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.2946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.2886e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.2827e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.2768e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.2707e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.2649e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.2593e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.2537e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.2483e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.2432e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.2383e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.2333e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.2282e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.2230e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.2179e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.2128e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.2076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.2024e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.1975e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.1925e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.1876e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.1828e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.1781e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.1734e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.1686e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.1638e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.1591e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.1544e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.1495e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.1447e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.1401e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.1354e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.1308e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.1263e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.1219e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.1174e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.1129e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.1084e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.1039e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.0994e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.0949e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.0903e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.0859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.0815e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 5.0771e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 5.0728e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 5.0686e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.0643e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.0600e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.0557e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.0515e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.0472e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.0429e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.0387e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.0345e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.0303e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.0261e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.0221e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.0180e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.0140e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.0099e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.0058e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.0017e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.9976e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.9936e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.9895e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.9856e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.9816e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 4.5066e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2169 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4984 Epoch 41/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 4.3624e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 4.4310e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.4003e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.4348e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 4.4037e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.3678e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.3356e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.3012e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.2629e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.2338e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.2140e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.1921e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.1736e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.1603e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.1478e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.1347e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.1207e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.1078e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.0961e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 4.0846e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 4.0721e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 4.0606e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.0514e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.0424e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.0343e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.0271e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.0206e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.0142e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.0077e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.0012e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.9957e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.9902e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.9844e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.9790e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.9741e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.9691e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.9645e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.9604e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.9566e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.9538e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.9506e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.9475e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.9443e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.9412e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.9376e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.9344e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.9313e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.9282e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.9254e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.9229e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.9204e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.9179e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.9153e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.9127e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.9102e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.9076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.9049e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.9022e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.8997e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.8971e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.8946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.8922e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.8898e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.8873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.8847e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.8820e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.8793e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.8765e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.8736e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.8708e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.8680e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.8652e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.8626e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.8601e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.8577e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.8552e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.8527e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.8502e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.8476e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.8450e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.8424e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.8398e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.8373e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.8348e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.8323e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.8299e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.8276e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.8252e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.8228e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.8203e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.8178e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.8154e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.8128e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.8103e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.8078e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.8053e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.8029e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.8006e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.7983e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.7959e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.7936e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.7912e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.7888e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.7864e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.7840e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.7816e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.7793e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.7769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.7746e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.7723e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.7701e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.7678e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.7656e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.7633e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.7610e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.7588e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.7565e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.7542e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.7519e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.7497e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 3.4802e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2236 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4985 Epoch 42/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.4687e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.5012e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.4793e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 3.4121e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.3403e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.2906e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.2560e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.2272e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.1986e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.1775e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.1631e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 3.1481e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 3.1369e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 3.1300e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 3.1240e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 3.1173e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 3.1106e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.1047e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.0994e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.0942e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.0885e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.0837e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.0801e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.0767e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.0736e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.0716e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.0700e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.0680e-05 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.0116e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.0105e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.0094e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.0085e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.0075e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.0064e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.0053e-05 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9836e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9826e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9816e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9806e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9796e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9786e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9777e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9768e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9759e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9749e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9739e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9729e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9719e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9709e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9698e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9688e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9678e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9668e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9658e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9648e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9638e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9628e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9617e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9607e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9596e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9586e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9575e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9565e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9555e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.8322e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2283 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4985 Epoch 43/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.0329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.2693e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.2588e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 3.1913e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 3.1277e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 3.0800e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 300ms/step - accuracy: 1.0000 - loss: 3.0421e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 300ms/step - accuracy: 1.0000 - loss: 3.0081e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.9721e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.9425e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.9200e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.8988e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8813e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8711e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8612e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8516e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8411e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8317e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8235e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8156e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8006e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.7946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.7884e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.7826e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.7793e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.7761e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.7724e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.7685e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.7645e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.7610e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.7572e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.7531e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.7490e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.7454e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.7415e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.7379e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.7353e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.7329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.7304e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.7277e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.7249e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.7224e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.7197e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.7169e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.7141e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.7115e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.7088e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.7063e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7044e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7027e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7009e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.6990e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.6970e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.6951e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.6932e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.6912e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.6894e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.6877e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.6860e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.6844e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.6832e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.6821e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.6809e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.6796e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.6783e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.6769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.6755e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.6740e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.6727e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.6714e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.6700e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.6688e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.6677e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.6666e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.6654e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.6643e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.6631e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.6620e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.6608e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.6596e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.6583e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.6571e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.6559e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.6546e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.6535e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.6523e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.6512e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.6500e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.6489e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.6477e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.6465e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.6453e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.6440e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.6428e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.6416e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.6405e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.6394e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.6383e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6373e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6362e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6351e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6340e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6318e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6307e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6297e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6286e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6275e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6265e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6255e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6245e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6235e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6225e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6214e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6204e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6193e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6182e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6172e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6161e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.4895e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2324 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 44/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 2.4398e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 2.5095e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.4981e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.4639e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.4236e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.3903e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.3725e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.3529e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.3422e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.3329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.3285e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.3225e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.3186e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.3174e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.3163e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.3141e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3109e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3073e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3038e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.3001e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.2957e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.2919e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.2891e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.2860e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.2833e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.2813e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.2796e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.2777e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.2753e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.2733e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.2717e-05 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.2097e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.2087e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.2077e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.2067e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.2057e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.2049e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.2040e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.2031e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.2021e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.2012e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.2003e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1993e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1983e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1974e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1965e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1955e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1938e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1930e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1922e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1914e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1905e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1897e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1889e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1881e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1865e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1857e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1849e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1842e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1835e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1827e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1820e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1812e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1805e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1798e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1790e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1783e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1776e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.0951e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2359 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 45/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 2.0897e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 2.1072e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.0998e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.0783e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.0514e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.0387e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.0306e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.0196e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.0076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.9999e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.9968e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.9924e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.9888e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.9870e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.9856e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.9859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.9854e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.9852e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.9851e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.9843e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.9825e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.9810e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.9805e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.9796e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.9789e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9786e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9784e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9779e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9774e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.9769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.9764e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.9756e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.9747e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.9737e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.9729e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.9719e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.9712e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.9706e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.9701e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.9696e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.9688e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.9680e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9672e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9663e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9654e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9645e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9638e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9631e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9625e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9621e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9616e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9611e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9605e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9600e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9595e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9589e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9583e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9577e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9572e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9567e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9561e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9558e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9554e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9549e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9544e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9539e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9534e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9529e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9523e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9518e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9513e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9507e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9502e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9497e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9493e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9488e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9482e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9477e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9472e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9467e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9461e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9456e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9451e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9446e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9441e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9436e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9432e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9427e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9422e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9417e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9412e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9407e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9402e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9397e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9392e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9386e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9381e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9377e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9372e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9367e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9362e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9356e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9351e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9346e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9340e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9334e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9323e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9318e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9313e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9308e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9303e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9298e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.9293e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.9287e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.9282e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.9277e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.9271e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.9266e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.9261e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.8626e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2387 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 46/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.7948e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.8230e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.8323e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.8155e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.7956e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.7811e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.7751e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.7725e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.7666e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.7628e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.7615e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.7608e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.7612e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.7644e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.7670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.7687e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.7692e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.7694e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.7694e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.7691e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.7678e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.7667e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.7663e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.7655e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7649e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7650e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7652e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7653e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7650e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7645e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7642e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.7636e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.7628e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.7622e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.7618e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.7612e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.7607e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.7604e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.7601e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.7597e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.7592e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.7586e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.7580e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.7573e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.7566e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.7558e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.7553e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.7546e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.7540e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.7536e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7531e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7526e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.7520e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.7513e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.7507e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7500e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7493e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7487e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7481e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.7475e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.7469e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.7464e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.7460e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.7455e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.7450e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.7444e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.7438e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.7433e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.7427e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.7421e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.7416e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.7411e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.7406e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.7402e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.7398e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.7394e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.7389e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.7384e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.7380e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.7375e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.7369e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.7364e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.7358e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.7353e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.7348e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.7343e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.7339e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.7334e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.7329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.7324e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.7319e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.7314e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.7308e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.7303e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.7298e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.7293e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.7288e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.7283e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.7278e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.7274e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.7269e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.7264e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.7259e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.7255e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.7250e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.7245e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.7241e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.7236e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.7232e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.7228e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.7224e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.7220e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.7215e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.7211e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.7207e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.7202e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.7198e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.7193e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.7189e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.7185e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.6671e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2416 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 47/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.6283e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.6679e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.6743e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.6613e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.6459e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6350e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.6273e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.6184e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.6076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.5992e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.5954e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.5908e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.5889e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.5900e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.5918e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.5929e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.5939e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.5942e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.5942e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.5935e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.5923e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.5909e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.5900e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.5895e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.5891e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.5894e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.5899e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.5901e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.5903e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.5903e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.5903e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.5901e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.5895e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.5889e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.5886e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.5882e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.5878e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.5877e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.5875e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.5872e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.5868e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.5864e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.5859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.5854e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.5847e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.5839e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.5833e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.5826e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.5820e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.5816e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.5813e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.5810e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.5806e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.5803e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.5798e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.5794e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.5789e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.5783e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.5778e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.5773e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.5769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.5766e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.5763e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.5760e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.5757e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.5754e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.5750e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.5747e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.5743e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.5739e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.5735e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.5731e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.5728e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.5724e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.5721e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.5718e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.5714e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.5710e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.5707e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.5703e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.5699e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.5695e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.5692e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.5688e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.5684e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.5681e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.5677e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.5674e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.5670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.5666e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.5662e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.5658e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.5653e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.5649e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.5645e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.5641e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.5636e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.5632e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.5628e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.5624e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.5620e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.5616e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.5611e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.5607e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.5603e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.5598e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.5594e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.5590e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.5586e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.5582e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.5579e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.5575e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.5571e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.5567e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.5564e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.5560e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.5557e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.5553e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.5549e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.5545e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 1.5101e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2439 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 48/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.7811e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.8021e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.7619e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.7254e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.6892e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6635e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6403e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6187e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.5969e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.5811e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.5699e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.5603e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.5525e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.5464e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.5422e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.5381e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.5336e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.5291e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.5255e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5217e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5180e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5148e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.5120e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.5093e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.5069e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.5050e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.5031e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.5012e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.4992e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.4972e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.4953e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.4935e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.4916e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.4898e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.4882e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.4865e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.4851e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.4840e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.4830e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.4821e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.4810e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.4799e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.4789e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.4779e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.4769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.4759e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.4751e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.4742e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.4733e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.4725e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.4718e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.4710e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.4702e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.4694e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.4687e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.4679e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.4672e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.4664e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.4657e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.4650e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.4644e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.4638e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.4633e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.4628e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.4622e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.4617e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.4611e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.4606e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.4600e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.4595e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.4589e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.4584e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.4578e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.4573e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.4568e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.4563e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.4557e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.4552e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.4546e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.4540e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.4534e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.4528e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4522e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4516e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4510e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4504e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.4499e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.4494e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.4488e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.4482e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.4477e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.4472e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.4466e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.4460e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.4455e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.4450e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.4444e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.4439e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.4434e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.4429e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.4424e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.4419e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.4413e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.4408e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.4403e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.4397e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.4392e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.4387e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.4381e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.4376e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.4371e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.4366e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.4361e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.4356e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.4351e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.4346e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.4341e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.4336e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.4331e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.4326e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.3739e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2461 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 49/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.3079e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.3625e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.3753e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.3670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.3524e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.3396e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3319e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3239e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3155e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3097e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3059e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3026e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3002e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2989e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2981e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2972e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2959e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2936e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2927e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2914e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.2910e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.2911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.2909e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2908e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2915e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - 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1.2913e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2912e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.2913e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.2913e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.2912e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.2911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.2910e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.2908e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.2907e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.2906e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.2905e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.2904e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.2905e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.2905e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.2904e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2903e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2901e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2899e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2898e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2895e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2892e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2890e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2887e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2885e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2884e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.2883e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.2881e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.2879e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.2877e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.2875e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.2873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.2870e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2867e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2865e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2862e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2860e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2858e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2856e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2853e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2851e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2849e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2847e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2846e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2843e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2841e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2839e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2837e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2835e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2833e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2832e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2830e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2828e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2826e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2824e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2822e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2819e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2817e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2814e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2812e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2809e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2807e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2805e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2802e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2800e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2798e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2795e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2793e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2790e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2787e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2785e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2782e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2780e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2778e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2776e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2773e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2771e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2769e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2767e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2764e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2762e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2760e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2757e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2755e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.2501e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2485 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 50/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.3736e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.3409e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3344e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3190e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.2998e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.2868e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.2751e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.2652e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.2554e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.2477e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.2426e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.2376e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2339e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2317e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.2297e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.2278e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.2256e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.2245e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.2235e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.2221e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.2204e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.2188e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.2178e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.2166e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.2157e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.2149e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.2141e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.2132e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.2122e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2112e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2103e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2095e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2085e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2077e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2070e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.2062e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.2055e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.2051e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.2046e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.2041e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.2037e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.2031e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.2025e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.2019e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.2012e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.2005e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2000e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1995e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1989e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1985e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1981e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1977e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1973e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1968e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1965e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1961e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1957e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1953e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1949e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1942e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1939e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1937e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1934e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1930e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1927e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1923e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1920e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1916e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1912e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1908e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1904e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1900e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1897e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1894e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1891e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1887e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1884e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1880e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1876e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1869e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1865e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1862e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1856e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1853e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1850e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1847e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1844e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1841e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1837e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1834e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1831e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1828e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1825e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1822e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1819e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1816e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1813e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1810e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1808e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1805e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1802e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1799e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1796e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1794e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1791e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1788e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1786e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1783e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1781e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1779e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1776e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1773e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1771e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1768e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1765e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1763e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1760e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.1439e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2507 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 51/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 1.1150e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.1921e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 1.2018e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.1942e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.1817e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.1706e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.1606e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1527e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1437e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1356e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1308e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1260e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1224e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1199e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1176e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1152e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1129e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1108e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1091e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1073e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1054e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.1039e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1027e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1016e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1007e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.1000e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.0995e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.0990e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.0983e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.0976e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.0971e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.0964e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0956e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0949e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0942e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0934e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0929e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0924e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0920e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.0916e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.0911e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.0906e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.0901e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.0900e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.0898e-05 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0886e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0885e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0883e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.0881e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.0880e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.0878e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.0877e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.0876e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.0875e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.0873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.0872e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.0871e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.0869e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.0867e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.0866e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.0864e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.0862e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.0860e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.0859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0857e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0856e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0854e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0852e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0850e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0848e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0846e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0844e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0841e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0839e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0837e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0835e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0833e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0831e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0829e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0827e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0825e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0822e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0820e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0818e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0816e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.0560e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2526 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 52/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.0545e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.0581e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0669e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0596e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0483e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0404e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0358e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0327e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0291e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.0267e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.0257e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.0242e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.0237e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.0240e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.0242e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.0241e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.0237e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.0230e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.0221e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0211e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0200e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0189e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0180e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0172e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0165e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.0160e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.0158e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.0155e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.0152e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.0148e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.0143e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.0140e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.0134e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.0130e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.0128e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.0125e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.0122e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.0121e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0121e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0119e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0117e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0115e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0113e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0111e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0108e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0106e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0104e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0102e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0100e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.0099e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.0097e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.0096e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.0095e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.0093e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.0091e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.0090e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.0087e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.0085e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.0082e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.0080e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.0078e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.0076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.0075e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.0074e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.0073e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.0072e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.0071e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.0070e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.0068e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.0067e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.0065e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.0064e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.0063e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.0062e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.0061e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.0060e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.0059e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.0057e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.0056e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0055e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0053e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0052e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0050e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0049e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0047e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0046e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0045e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0044e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0043e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0041e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0040e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0038e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0037e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0035e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0033e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0032e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0030e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0028e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0027e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0025e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0023e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0022e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0020e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0018e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0017e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0015e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0013e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0011e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0009e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0008e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0006e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0004e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0003e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0001e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.9995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.9977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.9959e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.9945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.9931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.9916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 9.8197e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2548 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 53/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.0171e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0171e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0200e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0188e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0116e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0074e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0024e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.9763e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.9186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.8811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.8574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.8254e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.8010e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.7938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.7881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.7775e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.7627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.7458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.7326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.7181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.7010e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.6875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.6783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.6673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.6580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.6500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 9.6429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.6351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.6262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.6176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.6090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.5996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.5890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.5789e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.5699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.5605e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.5517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.5446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.5380e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.5314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.5244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 9.5174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 9.5111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.5047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.4982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.4919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.4862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.4805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.4755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.4715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.4679e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.4640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.4609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.4576e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.4542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.4505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.4464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.4426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 9.4392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 9.4359e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 9.4329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 9.4303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 9.4277e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 9.4251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 9.4223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 9.4199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 9.4176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 9.4152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 9.4124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 9.4097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 9.4072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 9.4044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 9.4018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 9.3994e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 9.3970e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 9.3946e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.3922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.3898e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.3875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 9.3851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 9.3824e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 9.3799e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 9.3777e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 9.3753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 9.3732e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 9.3713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.3694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.3673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.3661e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.3647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.3634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.3618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.3602e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.3586e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.3571e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 9.3555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.3540e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 9.3526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 9.3513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 9.3500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 9.3485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 9.3469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 9.3453e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 9.3435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 9.3417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 9.3398e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 9.3380e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 9.3362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 9.3343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 9.3326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 9.3309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 9.3291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 9.3274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.3257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.3240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.3223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.3205e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.3187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.3169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.3151e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 9.0970e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2569 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 54/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 9.2246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 9.6736e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 9.8993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 9.8927e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 9.8279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 9.7693e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 9.7231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 9.7196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 9.6885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 9.6573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 9.6340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 9.6009e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 9.5801e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 9.5759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 9.5710e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 9.5671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 9.5565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.5424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.5260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.5065e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.4843e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.4631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.4451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.4259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.4088e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.3946e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.3823e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.3710e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.3586e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.3462e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.3339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.3217e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.3093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2356e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2123e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2043e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.1965e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.1893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.1816e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.1746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.1680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.1623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.1562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.1499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.1434e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.1372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.1311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.1245e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.1124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.1066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.1012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.0960e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.0909e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.0859e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.0806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.0752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.0699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.0653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.0604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.0555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.0508e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.0459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.0410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.0365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.0321e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.0277e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.0233e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.0190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.0148e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.0105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.0062e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.0018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 8.9976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 8.9934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 8.9893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 8.9854e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 8.9816e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 8.9777e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 8.9739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 8.9703e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 8.9667e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 8.9630e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 8.9593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 8.9558e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 8.9524e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 8.9489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 8.9456e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 8.9424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 8.9392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 8.9359e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 8.9325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 8.9291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 8.9257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 8.9223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 8.9188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 8.9152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 8.9118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 8.9083e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 8.9050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 8.9017e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 8.8986e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 8.8954e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 8.8922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 8.8890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 8.8858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 8.8827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 8.8795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 8.8763e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 8.8732e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 8.8701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 8.5089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2586 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 55/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 8.0121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 8.3331e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.5378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 8.5804e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 8.5633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.5360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 8.5022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.4827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.4480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.4162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.3962e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 8.3726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 8.3698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 8.3738e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 8.3784e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 8.3774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 8.3716e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 8.3641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 8.3566e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 8.3472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 8.3354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 8.3247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.3187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.3120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.3070e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.3041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.3010e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.2969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 8.2917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 8.2867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 8.2814e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.2755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.2685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.2623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.2571e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 8.2514e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 8.2485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 8.2481e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 8.2484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 8.2482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 8.2475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 8.2464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 8.2451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 8.2434e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 8.2411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 8.2387e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 8.2365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 8.2341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.2317e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.2297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.2278e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.2257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 8.2232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 8.2204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 8.2178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 8.2156e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 8.2130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 8.2105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 8.2084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 8.2064e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 8.2048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 8.2034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 8.2021e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 8.2010e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 8.1999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 8.1988e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 8.1977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 8.1965e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 8.1949e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.1934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.1922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.1908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.1902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.1895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.1889e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.1881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.1871e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.1859e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.1847e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.1834e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.1818e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.1801e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.1786e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.1770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.1758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.1748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 8.1737e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 8.1726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 8.1715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.1705e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.1695e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.1684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.1671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 8.1658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 8.1646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 8.1634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.1622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.1611e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.1600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.1588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.1575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.1561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.1547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.1532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.1515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.1499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.1483e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.1466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.1450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.1434e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.1419e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.1403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.1386e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.1370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.1354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.1337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.1320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.1303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.1288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.1272e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 7.9330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9773 - val_loss: 0.2606 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 56/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 8.1465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 8.2599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.2790e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.2105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.0920e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.0129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 7.9522e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 7.8938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 7.8367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 7.7940e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 7.7769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 7.7550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 7.7423e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 7.7366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 7.7317e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 7.7264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 7.7171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 7.7061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 7.6938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 7.6813e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 7.6674e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 7.6565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 7.6468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 7.6361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 7.6266e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 7.6190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 7.6122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 7.6061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 7.5993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 7.5930e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 7.5867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 7.5805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 7.5742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 7.5680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 7.5626e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 7.5572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 7.5519e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 7.5471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 7.5426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 7.5393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 7.5354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 7.5316e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 7.5278e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 7.5253e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 7.5224e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 7.5193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 7.5163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 7.5129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 7.5096e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 7.5070e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 7.5047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 7.5021e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 7.4992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 7.4963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 7.4936e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 7.4937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 7.4935e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 7.4932e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 7.4929e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 7.4923e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 7.4919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 7.4918e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 7.4918e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 7.4917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 7.4915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 7.4912e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 7.4909e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 7.5026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 7.5136e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 7.5241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 7.5343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 7.5440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 7.5533e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 7.5628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 7.5719e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 7.5805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 7.5887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 7.5966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 7.6046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 7.6354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 7.6649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 7.6933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 7.7210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 7.7476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 7.7736e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 7.7987e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 7.8232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 7.8467e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 7.8694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 7.8914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 7.9128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 7.9366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 7.9595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 7.9819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 8.0039e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 8.0253e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 8.0461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 8.0665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 8.0862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 8.1054e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 8.1239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 8.1419e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 8.1596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 8.1820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 8.2035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 8.2246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 8.2451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 8.2650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 8.2845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 8.3035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 8.3220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 8.3402e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 8.3580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 8.3753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 8.3940e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 8.4286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.4622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.4957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.5286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.5608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 1.2388e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.2588 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 57/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 9.2130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 9.9275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0197e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.2040e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3128e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.4069e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.0447e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.7416e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.2161e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.6595e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.9735e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 4.1987e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.3738e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.5033e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.5994e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.8236e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.0258e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.2054e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.3596e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.5067e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.6264e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.7376e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.8298e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.9083e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.0149e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.1098e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.2141e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.3722e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.5382e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.6971e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.8603e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 7.0151e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 7.1587e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 7.3199e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 7.4690e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 7.6175e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 7.7692e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 7.9160e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 8.0915e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 8.3042e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 8.5456e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 8.7992e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 9.0465e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 9.3048e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 9.5666e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 9.8573e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.0151e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.0479e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.0810e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.1152e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.1517e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.1926e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2361e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.2843e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.3327e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.3826e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 1.4363e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 1.4957e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 1.5589e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 1.6278e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 1.7002e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 1.7786e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 1.8615e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 1.9473e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.0364e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.1315e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.2287e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 0.9999 - loss: 2.3297e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 0.9999 - loss: 2.4356e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9999 - loss: 2.5468e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9999 - loss: 2.6652e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9999 - loss: 2.7898e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9999 - loss: 2.9240e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9999 - loss: 3.0668e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9999 - loss: 3.2139e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9999 - loss: 3.3631e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9999 - loss: 3.5205e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9999 - loss: 3.6841e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9999 - loss: 3.8550e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9999 - loss: 4.0307e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9999 - loss: 4.2169e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9999 - loss: 4.4237e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9999 - loss: 4.6506e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9999 - loss: 4.8960e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9999 - loss: 5.1616e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9998 - loss: 5.4557e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9998 - loss: 5.7742e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9998 - loss: 6.1114e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9998 - loss: 6.4866e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9998 - loss: 6.8978e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9998 - loss: 7.3307e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9998 - loss: 7.7797e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9997 - loss: 8.2517e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 0.9997 - loss: 8.7563e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 0.9997 - loss: 9.2879e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 0.9997 - loss: 9.8390e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 0.9997 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998   98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 0.9995 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9957 - loss: 0.0116 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4971 - val_accuracy: 0.9190 - val_loss: 0.7159 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4861 Epoch 58/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9874 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9874 - loss: 0.0307 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 302ms/step - accuracy: 0.9877 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 301ms/step - accuracy: 0.9882 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9885 - loss: 0.0283 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9888 - loss: 0.0277 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9890 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9892 - loss: 0.0266 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9894 - loss: 0.0262 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9896 - loss: 0.0258 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9897 - loss: 0.0254 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9898 - loss: 0.0251 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9900 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9900 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9901 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9902 - loss: 0.0242 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9903 - loss: 0.0240 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9904 - loss: 0.0237 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4929  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9905 - loss: 0.0235 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4929  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9906 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4930  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9907 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4930  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9908 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4931  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9908 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4931  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9909 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4932  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9910 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4932  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9911 - loss: 0.0222 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4933  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9911 - loss: 0.0221 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4933  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9912 - loss: 0.0219 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9912 - loss: 0.0218 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9913 - loss: 0.0216 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9914 - loss: 0.0215 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9914 - loss: 0.0214 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9915 - loss: 0.0212 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9915 - loss: 0.0211 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9916 - loss: 0.0210 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9916 - loss: 0.0208 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9917 - loss: 0.0207 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9917 - loss: 0.0206 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9918 - loss: 0.0205 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9918 - loss: 0.0204 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4938  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9919 - loss: 0.0203 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4938  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9919 - loss: 0.0202 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4938  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9920 - loss: 0.0201 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4939  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9920 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4939  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9921 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4939  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9921 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4940  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9921 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4940  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9922 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4940  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9922 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4940  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9923 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9923 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9924 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9924 - loss: 0.0190 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9924 - loss: 0.0189 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9925 - loss: 0.0189 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9925 - loss: 0.0188 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9925 - loss: 0.0187 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9926 - loss: 0.0186 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9926 - loss: 0.0185 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9927 - loss: 0.0184 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9927 - loss: 0.0183 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9927 - loss: 0.0182 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9928 - loss: 0.0182 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9928 - loss: 0.0181 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9928 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9929 - loss: 0.0179 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9929 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9929 - loss: 0.0178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9930 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9930 - loss: 0.0176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9930 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9930 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9931 - loss: 0.0174 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9931 - loss: 0.0173 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9931 - loss: 0.0173 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9932 - loss: 0.0172 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9932 - loss: 0.0171 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9932 - loss: 0.0171 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9932 - loss: 0.0170 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9933 - loss: 0.0169 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9933 - loss: 0.0169 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9933 - loss: 0.0168 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9933 - loss: 0.0168 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9934 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9934 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9934 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9934 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9935 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9935 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9935 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9935 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9936 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9936 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9936 - loss: 0.0161 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9936 - loss: 0.0161 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9936 - loss: 0.0160 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9937 - loss: 0.0160 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9937 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9937 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9937 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9937 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9938 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9938 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9938 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9938 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9938 - loss: 0.0155 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9939 - loss: 0.0155 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9939 - loss: 0.0154 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9939 - loss: 0.0154 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9939 - loss: 0.0154 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9939 - loss: 0.0153 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9940 - loss: 0.0153 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9940 - loss: 0.0152 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9940 - loss: 0.0152 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9940 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9940 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9940 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9941 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9941 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9941 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9960 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4968 - val_accuracy: 0.9735 - val_loss: 0.1576 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4962 Epoch 59/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9973 - loss: 0.0071 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9971 - loss: 0.0075 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9971 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9971 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9971 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9971 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9971 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9971 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9970 - loss: 0.0077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9970 - loss: 0.0078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9970 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9970 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9970 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9970 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9970 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9969 - loss: 0.0080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9969 - loss: 0.0082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976 - val_accuracy: 0.9735 - val_loss: 0.1761 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4964 Epoch 60/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9984 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9985 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9986 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 0.9987 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9988 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9988 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9988 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9988 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9988 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9988 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9988 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9988 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9989 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9989 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9989 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9989 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9989 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9989 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9989 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9989 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9990 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9990 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  43/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9991 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9991 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9991 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 0.9992 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9992 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9992 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9992 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9992 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9992 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 0.9993 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 0.9994 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 0.9994 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9997 - loss: 8.7424e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 - val_accuracy: 0.9766 - val_loss: 0.2008 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4980 Epoch 61/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 7.2922e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 6.9337e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.6488e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.4074e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.2083e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.0473e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 5.9260e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.8214e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.7166e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.6358e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.5771e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.5216e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.4749e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.4400e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.4102e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.3789e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.3468e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.3167e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.2894e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.2627e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.2351e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 5.2099e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 5.1886e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 5.1682e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 5.1496e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 5.1325e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 5.1167e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 5.1002e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 5.0833e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.0666e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.0502e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.0340e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.0174e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.0015e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.9874e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.9734e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.9600e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.9472e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.9349e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.9224e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.9100e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.8976e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.8859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.8750e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.8639e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.8531e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.8430e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.8327e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.8228e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.8133e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.8039e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.7944e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.7848e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.7754e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.7664e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.7578e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.7491e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.7404e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.7321e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.7237e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.7155e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.7077e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.7001e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.6925e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.6847e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.6771e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.6696e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.6620e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.6543e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.6469e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.6397e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.6325e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.6254e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.6184e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.6116e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.6048e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.5980e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.5913e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.5846e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.5780e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.5713e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.5647e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.5583e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.5518e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.5454e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.5390e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.5328e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.5264e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.5201e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.5138e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.5076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.5014e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.4951e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.4889e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.4828e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.4767e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.4707e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.4648e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.4589e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.4531e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.4472e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.4413e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.4355e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.4296e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.4238e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.4180e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.4122e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.4065e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.4008e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.3952e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.3896e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.3840e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.3784e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.3729e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.3674e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.3620e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.3566e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.3512e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.3458e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.3405e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 3.7068e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2238 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4984 Epoch 62/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 3.2553e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.2896e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 3.2870e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 3.2756e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.2232e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.1915e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.1640e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.1419e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.1116e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.0853e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.0663e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.0503e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.0370e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.0284e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.0208e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.0120e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 3.0019e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.9926e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.9835e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.9742e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.9643e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.9565e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.9501e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.9432e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.9370e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.9314e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.9258e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.9200e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.9138e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.9075e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.9017e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.8960e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.8898e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.8840e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.8792e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.8745e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.8703e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.8670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.8640e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.8606e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.8571e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.8534e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.8499e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.8462e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.8423e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.8392e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.8364e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.8335e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.8307e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.8284e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.8261e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.8237e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.8212e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.8186e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.8160e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.8134e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.8106e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.8079e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.8054e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.8027e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.8001e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.7977e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.7953e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7928e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7904e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7880e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.7856e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.7831e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.7805e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.7779e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.7754e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.7728e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.7703e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.7681e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.7659e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.7636e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.7613e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.7591e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.7568e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.7545e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.7522e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.7498e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.7475e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.7452e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.7430e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.7409e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.7388e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 2.7367e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 2.7346e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 2.7324e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 2.7303e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 2.7281e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 2.7259e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 2.7237e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 2.7215e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 2.7193e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 2.7172e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 2.7151e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 2.7131e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 2.7110e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 2.7088e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 2.7067e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 2.7046e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 2.7025e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 2.7003e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 2.6982e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.6962e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.6941e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.6920e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 2.6900e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 2.6880e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 2.6859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 2.6839e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 2.6818e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6798e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6777e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6756e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6735e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6714e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6693e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.4225e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2376 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4985 Epoch 63/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.4499e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.4014e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.3472e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 2.3100e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.2681e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.2384e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.2126e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.1894e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.1688e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.1546e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.1474e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.1385e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.1313e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.1253e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.1199e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.1132e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.1062e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.0993e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.0931e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.0865e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.0807e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.0748e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.0703e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.0654e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.0611e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.0575e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.0544e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.0509e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.0472e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.0435e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.0398e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.0362e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.0323e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.0287e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.0257e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.0227e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.0200e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.0175e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.0153e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.0140e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.0125e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.0110e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.0096e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.0081e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.0063e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.0046e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.0030e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.0014e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9997e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9982e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9968e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9953e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9938e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9923e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9907e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9891e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9875e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9844e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9829e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9814e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9800e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9786e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9772e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9757e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9743e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9728e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9713e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9698e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9683e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9655e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9642e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9630e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9619e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9606e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9594e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9582e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9569e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9556e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9543e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9530e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9518e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9506e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9494e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9482e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9471e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9461e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9452e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9441e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9431e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9421e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9411e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9400e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9390e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9380e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9370e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9360e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9351e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9341e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9330e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9320e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9310e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9299e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9288e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9278e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9267e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9257e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9247e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9236e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9226e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9216e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9206e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.9195e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.9185e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.9175e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.9164e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.9153e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.9142e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.9132e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.7873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2472 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 64/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.9093e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.8612e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.8325e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.7899e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.7476e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.7180e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.6948e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.6732e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.6507e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.6329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.6220e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.6113e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.6058e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.6020e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.5987e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.5945e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.5898e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.5850e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.5805e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5763e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5716e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5682e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5656e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5630e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5608e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5589e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5573e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5567e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5559e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.5549e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.5542e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.5538e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.5531e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.5525e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.5520e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.5515e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.5512e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.5511e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.5509e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.5507e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.5502e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.5496e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5492e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5489e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5483e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5479e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5476e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5473e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5471e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5469e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5467e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5466e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5463e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5460e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5456e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5452e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5449e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5445e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5442e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5438e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5435e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5432e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5428e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5425e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5420e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5416e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5411e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5406e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5400e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5395e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5390e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5385e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5380e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5376e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5372e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5367e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5362e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5357e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5352e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5347e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5341e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5336e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5331e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5325e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5320e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5315e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.5310e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.5305e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.5299e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5294e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5288e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5282e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5276e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.5270e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.5264e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.5257e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.5251e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.5246e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.5240e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.5234e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.5228e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.5221e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.5215e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.5209e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.5202e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.5196e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.5189e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.5183e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.5177e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.5170e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.5164e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.5158e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.5152e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.5145e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.5139e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.5132e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.5125e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.5118e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.5112e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.5105e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.4321e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2536 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 65/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 1.2858e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 1.0000 - loss: 1.3313e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.3338e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.3227e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.3038e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.3024e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.3024e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.2982e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.2909e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.2860e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 1.2848e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 1.2819e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 1.2800e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.2787e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.2779e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.2761e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.2737e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.2716e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.2700e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.2685e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.2664e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.2643e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.2627e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.2619e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.2613e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.2608e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.2604e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - 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1.2544e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.2543e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.2543e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.2546e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.2548e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.2548e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.2547e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.2546e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.2544e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.2542e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.2538e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.2534e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.2530e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.2526e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.2522e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.2519e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.2515e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.2511e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.2507e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.2504e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.2501e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 1.2497e-05 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.2418e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.2414e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.2410e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.2406e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.2401e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.2398e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.2394e-05 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.2363e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.2358e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.2354e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.2350e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.2345e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.2341e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.2337e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.2333e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.2329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.2325e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.2321e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.2318e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.2315e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.2311e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.2308e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 293ms/step - accuracy: 1.0000 - loss: 1.2305e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 293ms/step - accuracy: 1.0000 - loss: 1.2301e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 293ms/step - accuracy: 1.0000 - loss: 1.2298e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 293ms/step - accuracy: 1.0000 - loss: 1.2295e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 293ms/step - accuracy: 1.0000 - loss: 1.2292e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 293ms/step - accuracy: 1.0000 - loss: 1.2289e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 293ms/step - accuracy: 1.0000 - loss: 1.2286e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 293ms/step - accuracy: 1.0000 - loss: 1.2283e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 1.2280e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 1.2278e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.2275e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.2273e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.2271e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.2268e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 1.1985e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2595 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 66/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 1.1186e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 1.1605e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 1.1651e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.1592e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.1505e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.1432e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.1363e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.1442e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.1457e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.1466e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.1490e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.1492e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.1494e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1494e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1494e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1491e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1481e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1473e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1464e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1453e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1437e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1421e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1410e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1398e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1389e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1385e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1381e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1377e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1372e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1366e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1363e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1360e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1354e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1348e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1343e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1337e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.1332e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.1328e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.1323e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.1318e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.1313e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.1307e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.1301e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.1294e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.1286e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.1280e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1275e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1269e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1264e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1259e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1255e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1250e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1245e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1239e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1234e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1228e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1222e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1215e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1209e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1204e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1198e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1194e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1189e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1185e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1175e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1170e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1165e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1160e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1154e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1149e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1143e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1138e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1133e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1128e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1123e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1117e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1112e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1106e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1100e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1094e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1088e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1083e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1077e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1072e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1066e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1061e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1055e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1050e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1044e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1038e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1033e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1028e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1023e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1018e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1013e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1008e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1003e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.0998e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0993e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0988e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0983e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0978e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0974e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0969e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0964e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0960e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0956e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0951e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0947e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0943e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0939e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0934e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0930e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0926e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0921e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0917e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0912e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0908e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0903e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.0386e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2637 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 67/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.0261e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.0217e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0159e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0088e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 9.9615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 9.8774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.8014e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.7230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.6384e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.5759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.5377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.4956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.4676e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.4487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.4368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.4241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.4071e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.3903e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.3779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.3683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.3539e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.3413e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.3388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.3337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.3299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.3274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.3252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.3217e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.3167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.3109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.3058e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.3011e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2905e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2843e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2812e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2773e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2652e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.2409e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.2363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.2319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.2282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.2252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.2223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.2187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.2152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.2122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.2092e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.2057e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.2022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.1992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.1961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.1932e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.1909e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.1885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.1856e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.1827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.1796e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.1767e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.1738e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.1707e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.1675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.1647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.1616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.1590e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.1414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.1388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.1363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.1338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.1315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.1295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.1277e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.1257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.1235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.1213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.1191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.1169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.1143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 9.1118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.1096e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.1072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.1048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.1049e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.1050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.1050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.1047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.1042e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.1041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.1038e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.1032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.1026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.1021e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.1014e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.1008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.1001e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.0995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.0987e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.0978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.0968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.0958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.0947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.0934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.0921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.0910e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.0897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 8.9393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2685 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 68/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 9.0023e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 9.1108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 9.1248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 9.0934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.9768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 8.9074e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 8.8422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 8.7723e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 8.6991e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 8.6474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 8.6145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.5735e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.5467e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.5250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.5061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.4843e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.4636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.4427e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.4220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.4029e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.3817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.3615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.3452e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.3286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.3154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.3036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.2941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.2841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 8.2734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 8.2631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 8.2537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 8.2437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 8.2325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 8.2214e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 8.2117e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 8.2021e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 8.1935e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 8.1858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 8.1791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 8.1727e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 8.1664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 8.1599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 8.1535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 8.1493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 8.1440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 8.1385e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 8.1339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 8.1288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 8.1240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 8.1198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 8.1157e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 8.1114e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.1067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.1018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.0971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.0925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.0875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.0827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.0785e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.0741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.0700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.0662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.0625e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.0588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.0548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.0508e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.0469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.0430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.0388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 8.0349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 8.0314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 8.0278e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.0244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.0212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.0182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.0151e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 8.0120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 8.0089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 8.0060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 8.0032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 8.0001e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.9971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.9943e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.9915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.9889e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.9863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 7.9839e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 7.9813e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 7.9787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.9762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.9737e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.9713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.9688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.9662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.9640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.9615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.9592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.9570e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.9549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.9527e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.9504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.9481e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.9458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.9435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.9409e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.9384e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.9361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.9336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.9313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.9290e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.9268e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.9246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.9222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.9202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.9181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.9160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.9138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.9116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.9094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.9072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 7.6422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2725 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 69/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 8.6052e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.4842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.3407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.1833e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.0361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 7.9298e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 7.8355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 7.7480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 7.6582e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.5893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.5482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.5108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4808e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4237e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.4102e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.3969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.3857e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.3741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.3650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 7.3570e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 7.3533e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 7.3475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 7.3418e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.3398e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.3377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.3343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.3291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.3240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.3191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.3137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.3063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.2995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.2945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.2890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.2836e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.2788e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.2745e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.2754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.2754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.2748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.2741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.2731e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.2712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.2699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.2688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.2677e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.2664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.2655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.2648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.2640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.2629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.2616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.2600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.2582e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.2559e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.2535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.2514e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 7.2491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 7.2472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 7.2455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.2439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.2420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.2399e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.2395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.2391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.2400e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.2405e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.2409e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.2412e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.2414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.2417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.2421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.2425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.2429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.2430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.2429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.2428e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.2433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.2436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.2437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.2438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.2438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.2438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.2438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.2439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.2439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.2437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.2433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.2430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.2424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.2418e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.2412e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.2407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.2401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.2394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.2388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.2382e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.2374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.2365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.2355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.2345e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.2334e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.2322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.2309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.2297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.2286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.2276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.2267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.2258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.2250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.2241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.2232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.2223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.2213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.2202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.2190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.2179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.2169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 7.0907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2749 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 70/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 7.2314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 290ms/step - accuracy: 1.0000 - loss: 7.3092e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 7.2721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 7.1362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 7.0308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 6.9816e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 6.9298e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.8768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.8238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.7805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.7542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.7244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 6.7096e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 6.7000e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.6983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.6976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.6944e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.6972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.6986e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.6996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.6968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.6934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.6914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.6874e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.6842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.6829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.6811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.6787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.6758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.6726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.6698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.6665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.6618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.6574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 6.6548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 6.6518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 6.6490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 6.6469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.6448e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.6421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.6388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.6355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.6319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.6280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.6235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.6189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.6153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.6115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 6.6077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 6.6043e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 6.6011e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 6.5979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 6.5942e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 6.5911e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 6.5882e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.5854e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.5821e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.5792e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.5764e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.5734e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 6.5365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 6.5346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 6.5325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 6.5303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 6.5279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 6.5255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 6.5230e-06 - 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0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 6.4896e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.4873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.4851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.4829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.4806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.4784e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.4761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.4738e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.4715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.4691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.4668e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.4645e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.4621e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.4599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.4578e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.4558e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.4536e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.4515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.4493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.4472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.4450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.4428e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.4408e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.4388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.4368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 6.1955e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2788 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 71/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.9956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 6.0862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.2742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.2973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.2629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.2198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 6.1876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 6.1726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.1380e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 6.1089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 6.0900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 6.0664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 6.0501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 6.0369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 6.0261e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 6.0158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 6.0270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 6.0346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.0407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.0432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.0431e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.0443e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.0471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.0498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.0515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.0532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.0549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.0558e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.0552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.0541e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.0524e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.0499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.0461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.0433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.0426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 6.0422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 6.0421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 6.0423e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.0421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.0417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.0407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.0393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 6.0379e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.0362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.0337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.0313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.0292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.0276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.0263e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.0251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.0240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.0235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.0228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.0218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.0211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.0203e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.0191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.0180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.0174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.0167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.0161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.0157e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.0154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.0149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.0141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.0133e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.0124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.0113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.0100e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.0086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.0073e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.0058e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.0045e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.0034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.0024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.0012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.0001e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.9990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.9979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 5.9967e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 5.9953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 5.9938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.9926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.9913e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.9900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.9888e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 5.9876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 5.9863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 5.9849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 5.9835e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 5.9822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 5.9808e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.9792e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.9776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.9762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.9746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.9730e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.9715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.9699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.9683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.9667e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.9650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.9634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.9616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.9598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.9580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.9563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.9545e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.9528e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.9511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.9495e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.9479e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.9462e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 5.9446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.9429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.9412e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.9396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.9380e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.9364e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.9348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 5.7422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2808 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 72/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 6.3439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 6.0984e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.9812e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.0883e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 6.0686e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 6.0141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 5.9681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 5.9326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 5.8884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 5.8525e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 5.8335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 5.8072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 5.7908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.7742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.7592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.7436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.7267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.7116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.6976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 5.6839e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 5.6675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 5.6521e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 5.6404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 5.6294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.6200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 5.6113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.6050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - 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5.5594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.5545e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.5504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.5464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.5432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.5394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.5351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.5311e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.3958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.3942e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.3928e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.3914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.3899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 5.3886e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 5.3873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 5.3859e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.3847e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.3835e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.3822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.3810e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.3797e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.3783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.3769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.3756e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.3743e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.3730e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.3717e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.3705e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.3692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.3679e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 5.3665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 5.3651e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 5.3637e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.3623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.3608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.3594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.3580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 5.1871e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2836 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 73/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 36s 304ms/step - accuracy: 1.0000 - loss: 5.4430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 5.4153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.3830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.2868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.1895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.1414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 5.1197e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 5.0959e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 5.0626e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.0349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.0133e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 4.9920e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.9734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.9589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.9492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.9393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.9278e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.9169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.9077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.9000e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.8900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.8829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.8804e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.8764e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.8727e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.8722e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 4.8723e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 4.8734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 4.8747e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 4.8756e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 4.8765e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 4.8772e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 4.8766e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 4.8761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 4.8759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 4.8751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 4.8752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 4.8755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 4.8760e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 4.8784e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 4.8802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 4.8817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 4.8832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 4.8845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 4.8855e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 4.8863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 4.8873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 4.8902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 4.8930e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 4.8958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 4.8986e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 4.9012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 4.9031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 4.9048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 4.9066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 4.9087e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 4.9101e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 4.9114e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 4.9127e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 4.9137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 4.9147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 4.9156e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 4.9166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 4.9172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 4.9176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 4.9180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 4.9182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 4.9184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 4.9182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 4.9179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 4.9178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 4.9177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 4.9177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 4.9178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 4.9177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 4.9175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 4.9171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 4.9166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 4.9161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 4.9154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 4.9145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 4.9136e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 4.9128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 4.9118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 4.9109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 4.9100e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 4.9093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 4.9084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 4.9074e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 4.9063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 4.9053e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 4.9042e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 4.9030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 4.9017e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 4.9005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 4.8993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 4.8981e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 4.8973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 4.8965e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 4.8956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 4.8946e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 4.8936e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 4.8925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 4.8914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 4.8903e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 4.8891e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 4.8880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 4.8869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 4.8858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 4.8848e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 4.8838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 4.8828e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 4.8817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 4.8806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 4.8795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 4.8783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 4.8771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 4.8759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 4.8748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 4.8736e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 4.7353e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2862 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 74/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 4.8336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 4.9234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.9380e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.8471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.7505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.7089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.6703e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.6436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.6092e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.5772e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.5580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.5369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.5219e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.5151e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.5104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.5068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.5011e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.4943e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.4913e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.4890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.4850e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.4817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.4842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.4859e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.4877e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.4894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.4930e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.4960e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.4979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 4.4992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 4.4998e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 4.4401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 4.4393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 4.4386e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.4377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.4369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.4362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.4355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.4348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.4339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.4331e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.4322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.4313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.4304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.4294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.4285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.4275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.4266e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.4258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.4249e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.4241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.4232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.4224e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.4215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.4206e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.4197e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.4187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.4178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.4169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.4159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.4151e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.4142e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.4134e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.4125e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.4115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.4106e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.4096e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.4087e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.4077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.4068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.4059e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 4.2950e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2890 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 75/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 4.2166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 4.2324e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.3251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.2907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.2612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.2408e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.2253e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.2047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.1751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.1485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.1349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.1163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.1020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.0932e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.0860e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.0772e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.0667e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.0603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.0561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.0513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.0450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.0393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.0365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.0334e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.0314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.0310e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.0305e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.0292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.0276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.0258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.0242e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.0231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.0211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.0189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.0174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.0159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.0154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.0149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.0146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.0143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.0138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.0128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.0119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.0108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.0094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.0084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.0078e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.0068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.0063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.0060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.0057e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.0053e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 4.0047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 4.0040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 4.0033e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.0026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.0016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.0007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.0000e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 3.9992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 3.9983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 3.9976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.9969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.9963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.9955e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.9947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.9941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.9933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.9923e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.9914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.9905e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.9898e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.9890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.9885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.9881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.9877e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.9872e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.9869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.9866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.9863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.9858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.9853e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.9848e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.9843e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.9839e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.9835e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.9831e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.9825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.9819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.9812e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.9805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.9798e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.9791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.9783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.9777e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.9770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.9763e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.9756e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.9750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.9744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.9739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.9732e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.9726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.9720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.9712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.9704e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.9698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.9691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.9686e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.9680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.9675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.9671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.9666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.9662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.9657e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.9653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.9647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.9643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.9638e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.9633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 3.9003e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2917 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 76/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 5.6761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 5.3702e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.1248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.9117e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.7431e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.6094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.5061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.4135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.3295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 4.2636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 4.2178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 4.1768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.1444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.1327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.1225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.1109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.0975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.0833e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.0733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.0624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.0505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.0395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.0306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.0213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.0136e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.0071e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 4.0008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 3.9936e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 3.9853e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 3.9776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 3.9713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 3.9655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 3.9598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 3.9542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 3.9492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 3.9442e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 3.9399e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 3.9361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 3.9330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.9298e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.9264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.9229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.9194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.9160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.9121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.9081e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.9044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.9008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.8972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.8938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.8906e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.8876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.8844e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.8811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.8779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.8748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.8715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.8683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.8652e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.8623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.8594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.8566e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.8538e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.8510e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.8482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.8456e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 3.8429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 3.8403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 3.8376e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 3.8351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 3.8327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 3.8304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 3.8282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 3.8261e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 3.8241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 3.8227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 3.8213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 3.8199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 3.8186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.8173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.8159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.8144e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.8130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 3.8115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 3.8100e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 3.8086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 3.8073e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 3.8060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 3.8046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 3.8032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 3.8018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 3.8005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 3.7990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 3.7975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 3.7961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 3.7946e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 3.7933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 3.7919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 3.7906e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 3.7893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 3.7879e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 3.7865e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 3.7851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 3.7836e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 3.7822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 3.7809e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 3.7796e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 3.7782e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 3.7771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 3.7761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 3.7750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 3.7740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 3.7730e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 3.7719e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 3.7709e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 3.7698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 3.7687e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 3.7676e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 3.7666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 3.7656e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 3.6432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2937 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 77/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 302ms/step - accuracy: 1.0000 - loss: 4.6868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 4.5000e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.3398e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.2289e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.1078e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.0370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.9799e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.9324e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.8898e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.8525e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.8215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.7952e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.7733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.7540e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.7397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.7271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 3.7137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 3.7006e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 3.6881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 3.6763e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 3.6636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 3.6523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 3.6426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 3.6330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 3.6243e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 3.6167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 3.6099e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 3.6030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 3.5966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 3.5908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 3.5852e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 3.5799e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 3.5742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 3.5691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 3.5646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 3.5602e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 3.5560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 3.5523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 3.5490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.5454e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.5414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.5381e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.5347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.5314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.5283e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.5253e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.5226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.5198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.5171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.5146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.5126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.5106e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.5084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.5063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.5041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.5018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.4993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.4974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.4956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.4937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.4921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.4908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.4894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.4880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.4866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.4851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 3.4836e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 3.4822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 3.4806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 3.4793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 3.4779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 3.4765e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 3.4752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 3.4742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 3.4733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 3.4724e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 3.4715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 3.4704e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 3.4694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.4685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.4673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.4661e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.4652e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.4642e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.4634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.4625e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.4619e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.4612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.4604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.4596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.4589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.4581e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.4573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.4567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.4560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.4553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.4548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.4542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.4537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.4531e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.4525e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.4518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.4511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.4505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.4498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.4490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.4484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.4476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.4469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.4462e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.4455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.4448e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.4440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.4432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.4425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.4417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.4408e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.4399e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.4391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.4382e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 3.3355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2959 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 78/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 4.3591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 4.3502e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.2919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.1915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.0685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.9653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.8820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.8114e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.7496e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.6948e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.6510e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.6153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.5845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.5653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.5506e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5102e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.4974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 3.4865e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 3.4752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 3.4652e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 3.4566e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 3.4478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 3.4402e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 3.4333e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 3.4270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 3.4214e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.4152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.4089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.4028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.3966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.3901e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.3837e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.3779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.3722e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.3672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.3625e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 3.3578e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 3.3532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 3.3484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 3.3439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 3.3394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 3.3348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 3.3299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.3255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.3215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.3176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.3141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.3109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.3080e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.3052e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.3024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.2996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.2971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.2945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.2918e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.2891e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.2867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.2842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.2819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.2819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.2820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.2819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.2817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2814e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2799e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.2791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.2784e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.2776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 3.2769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 3.2762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 3.2755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2730e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2714e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2705e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2696e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2679e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2670e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2638e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.2630e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.2622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.2614e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.2606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.2598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.2590e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.2582e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.2575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.2568e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.2561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.2554e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.2547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.2539e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.2531e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.2523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.2514e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.2506e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2481e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2473e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.2443e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.2435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.2428e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.2421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.2414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.2407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.2400e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 3.1556e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2983 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 79/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.2603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.2529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.2396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.2260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.1852e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.1530e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.1369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.1156e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.0895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.0671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.0544e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.0401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.0287e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.0213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.0171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.0129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.0072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 3.0024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.9972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.9918e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.9858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.9806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.9771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.9733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.9699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.9669e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.9644e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - 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2.9588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.9583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.9580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.9576e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.9569e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.9565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.9559e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.9553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.9547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.9543e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.9545e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.9547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.9549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.9550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.9550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.9549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.9549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.9548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.9547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.9546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.9546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.9544e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.9540e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.9546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.9552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.9557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.9562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.9568e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.9574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.9579e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.9581e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.9583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.9586e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.9587e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.9589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.9591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.9594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.9595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.9596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.9597e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.9598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.9598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.9597e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.9595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.9593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.9590e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.9587e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.9583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.9580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.9576e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.9572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.9571e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.9570e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.9569e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.9567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9559e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9554e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9551e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9543e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9540e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9538e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9545e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9558e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9564e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9570e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9579e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9587e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9607e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9611e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9614e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9619e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9630e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 3.0060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2993 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 80/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 3.3894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 3.3774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.3653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.4740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.4762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.4672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.4604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.4481e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.4206e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.3931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.3916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.3832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.3745e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.3653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.3559e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.3436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.3306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.3185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.3071e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.2957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.2846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.2749e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.2662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.2572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.2484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.2407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.2335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.2259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.2179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.2104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.2031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.1958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.1880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.1804e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.1736e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.1671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.1609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.1549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.1491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.1432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.1374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.1322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.1271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.1220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.1170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.1124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 3.1081e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 3.1038e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 3.0997e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 3.0964e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 3.0932e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 3.0900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.0867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.0834e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.0802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.0771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 3.0738e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 3.0705e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 3.0673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 3.0641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 3.0611e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 3.0582e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 3.0557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 3.0531e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 3.0503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 3.0476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.0449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.0422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.0394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.0366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.0340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.0314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.0290e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.0267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.0244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.0222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.0199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.0177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.0155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.0133e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.0111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.0089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.0067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.0046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.0025e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.0005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.9985e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.9965e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.9945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9924e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9904e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9883e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.9862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.9802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9786e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.9756e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.9696e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.9650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9621e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9607e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9568e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.9555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9530e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.9517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9479e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.9467e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.7958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3025 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 81/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.3609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.4382e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.3827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.3725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.3121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.2675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.2315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.1944e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.1565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.1286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.1040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.0805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.0605e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.0433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.0268e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 3.0113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.9957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.9819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.9695e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.9568e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.9449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.9342e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.9245e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.9147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.9059e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.8975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.8897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.8830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.8760e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.8697e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.8633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.8570e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.8505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.8463e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.8427e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.8391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.8356e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.8325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.8294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.8263e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.8235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.8206e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.8177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.8148e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.8118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.8087e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.8059e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.8030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.8003e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.7977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.7952e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.7926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.7899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 2.7872e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 2.7849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 2.7825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.7799e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.7773e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.7752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.7729e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.7708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.7687e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.7668e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.7648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.7627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.7606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.7624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.7640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.7653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 2.7666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 2.7680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 2.7693e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 2.7707e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 2.7725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 2.7775e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 2.7822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 2.7880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 2.7936e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 2.9229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.0473e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.1685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.2925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 3.4142e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 3.5346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 3.6521e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 3.7820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 4.0068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 4.2255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 4.4628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 4.7366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 5.1014e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 5.4658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 5.9233e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 6.4956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 7.0867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 7.7273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 8.3864e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 9.1892e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 1.0101e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.1032e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.2071e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.3391e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.4799e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 1.6447e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 1.8280e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 2.0355e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.2750e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.5372e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.8272e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 3.1602e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 3.5209e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 3.8968e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 4.3133e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 4.7670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 5.2467e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 5.7516e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 6.2873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 6.8688e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 7.5047e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.1744e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 0.9997 - loss: 8.7863e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 - val_accuracy: 0.9752 - val_loss: 0.2331 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4977 Epoch 82/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9962 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9961 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9960 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9962 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9962 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9963 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9963 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9964 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9964 - loss: 0.0096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9964 - loss: 0.0096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9964 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9964 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9963 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9963 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9963 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9963 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9963 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9963 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9962 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9962 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9962 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9962 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9962 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9961 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9961 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9960 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9960 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9960 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9960 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9960 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9960 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9959 - loss: 0.0109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9959 - loss: 0.0108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9960 - loss: 0.0107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9960 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9960 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9960 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9960 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9960 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9960 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9960 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9960 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9961 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9961 - loss: 0.0105 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9961 - loss: 0.0104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9961 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9961 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4972  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9961 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9961 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9961 - loss: 0.0103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9961 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9962 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9962 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9962 - loss: 0.0102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9962 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9962 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9962 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9962 - loss: 0.0101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9962 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9962 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9962 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9962 - loss: 0.0100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9963 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9963 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9963 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9963 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9963 - loss: 0.0099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4973 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9963 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9963 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9963 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9963 - loss: 0.0098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9963 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9963 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9964 - loss: 0.0097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4974 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980 - val_accuracy: 0.9733 - val_loss: 0.1991 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4969 Epoch 83/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9984 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9984 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9984 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9984 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9984 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9984 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9984 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9984 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9984 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9984 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9983 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9982 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9982 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985 - val_accuracy: 0.9737 - val_loss: 0.2089 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4970 Epoch 84/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9990 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9990 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9990 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9990 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9995 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 - val_accuracy: 0.9761 - val_loss: 0.2180 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4980 Epoch 85/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.4150e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.4268e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.4121e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.3455e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.2813e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.2313e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.1919e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 3.1543e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.1152e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.0835e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.0574e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.0312e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.0104e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.9940e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.9791e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.9642e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.9490e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.9372e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.9257e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.9142e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.9026e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8921e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8824e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8725e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8632e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.8547e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.8465e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.8378e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.8287e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.8202e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.8119e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.8036e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7950e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7866e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7792e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7718e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7647e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7582e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7520e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.7458e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.7395e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.7345e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.7294e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.7240e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.7186e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.7134e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.7082e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.7031e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.6981e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.6933e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.6885e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.6837e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.6787e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.6739e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.6692e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.6644e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.6594e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.6546e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.6499e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.6452e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.6407e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.6362e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.6317e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.6272e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.6227e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.6182e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.6139e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.6095e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.6050e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.6006e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.5963e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.5919e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5876e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5834e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5792e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5751e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5710e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5671e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5632e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.5593e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.5553e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.5513e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.5474e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.5435e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.5396e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.5358e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.5319e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.5281e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.5242e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.5204e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.5166e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.5128e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.5090e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.5052e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.5014e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.4977e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.4941e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.4904e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.4868e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.4832e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.4796e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.4760e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.4724e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.4688e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.4651e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.4615e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.4580e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.4544e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.4509e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.4474e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.4439e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.4405e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.4370e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.4336e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.4301e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.4267e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.4233e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.4203e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.4173e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.4142e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 2.0543e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9767 - val_loss: 0.2360 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4984 Epoch 86/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.5765e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.5807e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.5844e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.5562e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.5285e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.5110e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4995e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4869e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4730e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.4616e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.4537e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.4448e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.4377e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.4330e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.4287e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.4234e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.4175e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.4122e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.4076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.4030e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.3982e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.3938e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3902e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3865e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3832e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3805e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.3780e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.3759e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.3735e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.3712e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.3691e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.3670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.3646e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.3623e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.3603e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.3582e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 1.3566e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 1.3552e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 1.3538e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.3523e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.3507e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.3493e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.3479e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.3466e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.3452e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.3438e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.3425e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.3411e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.3397e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.3385e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.3374e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.3363e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.3351e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.3338e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.3326e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.3313e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.3300e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.3286e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.3274e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.3261e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.3249e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.3237e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.3226e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.3215e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.3204e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.3192e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.3181e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.3170e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.3158e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.3147e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.3135e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.3123e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.3112e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.3101e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.3090e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.3078e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.3067e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.3056e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.3045e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3035e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3023e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3012e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3001e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.2990e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.2979e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.2968e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.2957e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.2946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.2935e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2924e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2913e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2902e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2891e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2880e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2868e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2857e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2846e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2835e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2824e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2813e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2803e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2792e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2781e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2771e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2761e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2750e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2740e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2730e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2720e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2710e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2700e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2690e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2680e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2660e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2649e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2639e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2629e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2619e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2609e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.1423e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9767 - val_loss: 0.2474 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4985 Epoch 87/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 1.0327e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 1.0000 - loss: 1.0346e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 1.0265e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.0058e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 9.8561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 9.7204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 9.6342e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 9.5876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 9.5209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 9.4827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 9.4603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 9.4279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 9.4143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 9.4038e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.3956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.3842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.3694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.3552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.3425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.3273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.3078e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.2895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.2751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.2596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.2457e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 9.2346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 9.2246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 9.2168e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 9.2065e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 9.1969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 9.1878e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 9.1776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 9.1682e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 9.1648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 9.1868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.2050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.2215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.2373e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 9.2511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 9.2622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 9.2708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 9.2786e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 9.2856e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 9.2911e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 9.2943e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 9.2967e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 9.2992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 9.3007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 9.3023e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 9.3041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 9.3176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 9.3294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 9.3399e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 9.3491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 9.3581e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.3661e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.3727e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.3793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.3855e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.3906e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.3950e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.3993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.4031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.4067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.4097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.4121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.4139e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.4153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.4163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 9.4174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 9.4184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 9.4211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 9.4234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 9.4256e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 9.4275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 9.4288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.4295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.4298e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.4300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 9.4300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 9.4295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 9.4288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 9.4279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 9.4280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 9.4280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 9.4278e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.4274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 9.4267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.4256e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.4242e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.4226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.4207e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.4186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.4166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.4144e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.4120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.4096e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.4073e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.4048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.4022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.3994e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.3964e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.3933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.3900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.3867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.3834e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.3802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.3768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.3734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.3699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.3664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.3628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.3591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.3553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.3519e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.3485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.3449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.3414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.3378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.3341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 8.8919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9767 - val_loss: 0.2563 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 88/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 7.4234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 7.5241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.4724e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.5593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 7.5369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 7.5008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 7.4771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 7.4596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 7.4269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 7.3983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 7.3793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.3527e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 7.3341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 7.3247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 7.3190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.3139e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.3015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.2911e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.2817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.2801e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.2741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.2714e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.2699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.2654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.2620e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.2600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.2575e-06 - mean_absolute_error: 0.5000 - 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mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.2276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.2220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.2165e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.2119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.2081e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 7.2036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 7.1984e-06 - mean_absolute_error: 0.5000 - 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mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.0082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.0048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.0015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 6.9981e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 6.9948e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 6.9914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.9882e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.9850e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.9819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.9787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.9754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.9721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.9688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.9658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.9628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.9599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.9571e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.9542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.9513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.9485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.9456e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.9426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.9394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.9363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.9332e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.9300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.9266e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.9233e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.9200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.9166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 6.5147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9767 - val_loss: 0.2630 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 89/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 5.5470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 5.8942e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.9643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.9700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 5.8984e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 5.9650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 6.0172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 6.0432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 6.0344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 6.0238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 6.1817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 6.2939e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 6.3769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 6.4424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 6.4900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 6.5214e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 6.5417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.5549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.5648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.5692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.5681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.5649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.5610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.5537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.5460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.5397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.5348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 6.5300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.5231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.5302e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 6.5356e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.5389e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.5401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.5405e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 6.5406e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 6.5397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 6.5384e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 6.5367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.5347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.5314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.5298e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.5278e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.5258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.5230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.5193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.5158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.5124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.5084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.5045e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.5006e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.4966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.4924e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.4881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.4838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.4795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.4749e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.4699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.4647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.4598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.4546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.4493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.4440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.4389e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.4338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.4284e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.4232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.4180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.4125e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.4069e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.4013e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.3958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.3902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.3848e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.3793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.3740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.3688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.3634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.3579e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.3526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.3472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.3415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.3360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.3305e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.3248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.3193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.3139e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.3084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.3032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.2978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.2924e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.2871e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.2823e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.2774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.2725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.2677e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.2629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.2581e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.2535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.2490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2305e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.1974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.1928e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.1881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.1835e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.1789e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 6.1744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 6.1702e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.1660e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.1617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.1575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.1533e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 5.6534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2682 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 90/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 5.9872e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.8692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.7452e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.7128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.6182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 5.5317e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.4549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.4064e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 5.3535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.3077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 5.2776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 5.2513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.2311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.2145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.2004e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.1841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 5.1665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 5.1523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.1382e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.1234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.1068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 5.0915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 5.0790e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 5.0666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.0553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.0455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.0366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.0313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.0247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.0188e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.7900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 4.7868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 4.7835e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 4.7804e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 4.7772e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 4.7741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 4.7711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 4.7685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 4.7659e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 4.7632e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 4.7605e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 4.7578e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 4.7552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 4.7524e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 4.7497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 4.7470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 4.7444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 4.7418e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 4.7393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 4.7369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.7345e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.7320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.7296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.7271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.7246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.7225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.7204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.7183e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.7162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.7141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.7120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.7098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.7077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.7056e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.7034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.7012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.6989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.6966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.6944e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.6922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.6899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 4.4179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2736 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 91/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.0240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 4.8156e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 4.6676e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 4.5557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 4.4553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 4.3961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 4.3663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 4.3415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 4.3167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 4.2934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 4.2778e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 4.3093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 4.3320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 4.3517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.3663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.3766e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 4.3808e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 4.3826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.3835e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.3826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.3780e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 4.3734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.3721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.3688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.3670e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.3653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.3632e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.3600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.3557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.3509e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.3475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.3439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.3395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.3355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.3317e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.3275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.3229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 4.3199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.3169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.3135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.3096e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.3056e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.3018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.2982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.2942e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.2906e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.2873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.2846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.2819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.2797e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.2775e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.2751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.2724e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.2695e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.2666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 4.2646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 4.2621e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 4.2597e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 4.2573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 4.2549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 4.2526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 4.2505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 4.2484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 4.2461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 4.2438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 4.2413e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 4.2390e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 4.2365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 4.2338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 4.2311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 4.2285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 4.2259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 4.2235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 4.2211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 4.2188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 4.2167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 4.2144e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 4.2121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 4.2097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 4.2073e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 4.2048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 4.2022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 4.1998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 4.1972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 4.1947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 4.1922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 4.1899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 4.1876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 4.1853e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 4.1830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 4.1806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 4.1783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 4.1759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 4.1735e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 4.1713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 4.1691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 4.1669e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 4.1648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 4.1627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 4.1606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 4.1584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 4.1562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 4.1540e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 4.1518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 4.1501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 4.1483e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 4.1476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 4.1468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 4.1459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 4.1450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 4.1441e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 4.1432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 4.1422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 4.1413e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 4.1404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 4.1395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 4.1387e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 4.1378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 4.1370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 4.1361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 4.0282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2778 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 92/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.2577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.3588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 3.4034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.3974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 3.3687e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.3599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 3.3712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 3.3805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.3754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 3.3784e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 3.3834e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.3830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.3843e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.3881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.3930e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.3975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.3994e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.4007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.4036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.4046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 3.4043e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.4036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.4040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.4050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.4069e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 3.4089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 3.4108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 3.4118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.4119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.4116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.4115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.4112e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.4098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.4087e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.4078e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.4065e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.4054e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.4047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.4040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.4040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.4036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.4030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.4027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.4022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.4015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.4009e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.4008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.4003e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.3998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.3996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.3994e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.3989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.3982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.3972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.3963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.3956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.3945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.3936e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.3926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.3915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.3904e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.3895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.3887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.3877e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.3867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.3855e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.3844e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.3832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.3819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.3808e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.3798e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.3787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.3776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.3765e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.3755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.3744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.3732e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.3720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.3709e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.3698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.3685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.3672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.3659e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.3646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.3634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.3622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.3610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.3598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.3584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.3575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.3567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.3557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.3546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.3535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.3525e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.3514e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.3504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.3494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.3486e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.3478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.3469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.3460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.3453e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.3445e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.3436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.3428e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.3420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.3412e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.3403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.3394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.3386e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.3377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.3368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.3359e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.3351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.3342e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.3334e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.3325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.3316e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.3308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 3.2296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2822 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 93/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.2209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.2616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.2984e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.2892e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.2749e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.2527e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.2334e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.2181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.1990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.1858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.1751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.1862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.1963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.2060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.2210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.2304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.2355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.2416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.2464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.2487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.2499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.2507e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.2532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.2563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.2622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.2678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.2721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.2766e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.2800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.2825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.2846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.2862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.2866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.2867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.2866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.2858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.2850e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.2850e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 3.2850e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.2844e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.2833e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 3.2819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.2805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.2793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.2776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 3.2759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 3.2741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 3.2720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 3.2700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 3.2682e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 3.2666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 3.2648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.2626e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.2609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.2592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.2575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 3.2556e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 3.2537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 3.2521e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 3.2504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 3.2487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 3.2471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 3.2455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 3.2438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 3.2418e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 3.2401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.2384e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.2369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.2352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.2335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.2319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.2302e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.2285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.2269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.2254e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.2237e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.2220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.2202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.2184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.2166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.2146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.2128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.2109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.2090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.2070e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.2051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.2032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.2012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.1992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.1972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.1953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.1933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.1914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.1896e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.1878e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.1863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.1847e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.1832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.1817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.1802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.1786e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.1780e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.1774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.1768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.1760e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.1752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.1745e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.1737e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.1729e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.1721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.1713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.1707e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.1700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.1694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.1687e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.1679e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.1671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.1663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.1656e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.1649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 3.0827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2857 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 94/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 2.6129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 2.7576e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 2.7675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.7758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.7796e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.7704e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.7786e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.7777e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.7651e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.7553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.7494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.7422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 2.7372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 2.7342e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 2.7320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.7296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.7251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.7224e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.7204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.7306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.7374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.7430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.7491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.7537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.7581e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.7618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.7649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.7671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.7680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.7684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.7690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.7692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7689e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.7692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.7689e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.7691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.7692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.7692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.7688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.7683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.7680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.7675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.7670e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.7663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.7656e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.7701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.7741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.7779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.7814e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.7846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.7874e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.7900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.7926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.7949e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.7972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.7994e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.8015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.8033e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.8051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.8066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.8080e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.8093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.8104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.8113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.8123e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.8131e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.8138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.8146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.8153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.8160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.8165e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.8170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.8174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.8177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.8179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.8179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.8180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.8181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.8183e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.8185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.8187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.8189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.8200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.8210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.8225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.8239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.8252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.8264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.8300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.8334e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.8371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.8406e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.8441e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.8474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.8505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.8534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.8563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.8590e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.8616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.8640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.8664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.8688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.8711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.8734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.8755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.8776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.8795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.8815e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.8833e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.8851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.8868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.8884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.8900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.8915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 3.0712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2882 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 95/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 2.4744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 2.6238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.7595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.8832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.9077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.9128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.9185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.9136e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.9007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.8886e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.8823e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.8708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8607e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.7992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.7946e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.7916e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.7341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.7264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.7242e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.7220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.7198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.7173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.7148e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.7124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.7099e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.7074e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.7051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.7029e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.7022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.6999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.6990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.6979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.6968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.6958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.6948e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.6937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.6928e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.6917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.6907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.6895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.6893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.6890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.6886e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.6881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.6875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.6869e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.6817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.6810e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.6803e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.6796e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.6789e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.6780e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.6772e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.6764e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.6756e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6729e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6607e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6597e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6587e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.6557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.5351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2904 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 96/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.8529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.9792e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.0231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.0524e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.0503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.0477e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.0553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.0600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.0593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.0678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.0805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.0883e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.0962e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.1041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.1117e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.1174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.1206e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.1229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.1260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.1283e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.1291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.1299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.1308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.1309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.1326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.1351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.1374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.1447e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.1512e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.1572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.1629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.1678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.1717e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.1751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.1787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.1817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.1845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.1871e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.1895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.1914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.1931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.1944e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.1957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.1968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.1976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.1982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.1990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.1998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.2006e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.2014e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.2022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.2028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.2032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 2.2036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 2.2043e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 2.2053e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.2061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.2068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.2089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.2109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.2130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.2151e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.2171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.2189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.2205e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.2220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.2234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.2247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.2258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 2.2269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 2.2279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 2.2289e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 2.2297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 2.2305e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 2.2314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 2.2321e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 2.2327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 2.2332e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 2.2337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 2.2343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 2.2347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 2.2351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 2.2355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 2.2357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 2.2360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 2.2362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 2.2365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 2.2367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 2.2368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 2.2370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 2.2373e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 2.2374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 2.2375e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 2.2376e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 2.2377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 2.2377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 2.2377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 2.2378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 2.2378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 2.2378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 2.2378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 2.2377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 2.2377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 2.2376e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 2.2375e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 2.2374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.2373e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.2371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 2.2370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 2.2368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 2.2367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 2.2365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 2.2363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 2.2360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 2.2360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 2.2359e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 2.2358e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 2.2357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 2.2356e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 2.2355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 2.2173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2935 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 97/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.1920e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.1410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.1953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.2074e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.2105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.2063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.2077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.2032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.1887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.1790e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.1727e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.1697e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.1667e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.1654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.1645e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.1640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.1658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.1664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.1666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.1663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.1658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.1655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.1657e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.1650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.1650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.1652e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.1654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.1648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.1643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.1635e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.1629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.1642e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.1655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.1669e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.1685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.1696e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.1703e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.1709e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.1713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.1713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.1712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.1709e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.1705e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.1700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.1692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.1684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.1678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.1670e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.1661e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.1653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.1645e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.1636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1613e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.1579e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.1572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.1567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.1560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.1553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.1550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.1547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.1542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.1536e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.1530e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.1524e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.1518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.1511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1488e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.1472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.1464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.1457e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.1449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.1441e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.1434e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1418e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1408e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1398e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1390e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1386e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1381e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1373e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1359e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1334e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1328e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1323e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1312e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1307e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1301e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1263e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.0497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2964 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 98/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 2.2084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.1970e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.1321e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.0651e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.0061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.9648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.9491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.9297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.9098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.8945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.8854e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.8756e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.8686e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.8631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.8584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.8544e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.8509e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.8489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.8490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.8528e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.8551e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.8566e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.8580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.8585e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.8590e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.8596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.8601e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.8599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.8595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.8594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.8591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.8586e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.8575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.8566e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.8559e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.8548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.8539e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.8532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.8526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8520e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8512e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8502e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8483e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8457e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8448e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.8430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.8422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.8413e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.8404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.8394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.8385e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.8379e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.8371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.8364e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.8357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.8349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.8343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.8336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.8330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.8324e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.8317e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.8310e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.8306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.8303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.8300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.8296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.8293e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.8289e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.8285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.8282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.8279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.8275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.8271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.8267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.8263e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.8259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.8254e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.8250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.8246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.8242e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.8238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.8235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8233e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8219e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.8212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.8208e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.8204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.8200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.8196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.8192e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.8188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.8184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.8180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.8177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.8173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.8170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.8167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.8164e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.8161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.8158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.8155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.8153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.8150e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.8147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.8144e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.8141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.8137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.8135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.8133e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.8131e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.8129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.7907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2994 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 99/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.7086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.7349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.7230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.6890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.6548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.6411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.6314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.7097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.7577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.7894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.8138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.8314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.8470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.8592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.8680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.8736e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.8761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.8896e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.9006e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.9084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.9131e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.9174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.9211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.9230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.9248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.9260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.9270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.9276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.9285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.9287e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.9282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.9273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.9264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.9251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.9235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.9219e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.9200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.9192e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.9181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.9189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9197e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9133e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9013e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9001e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.8989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.8976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.8963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.8951e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.8937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.8924e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.8911e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.8898e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.8884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.8871e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.8858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.8844e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.8829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.8815e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.8800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.8785e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.8770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.8755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.8740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.8726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.8712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.8699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.8686e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.8673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.8658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.8645e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.8631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.8617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.8602e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.8588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.8574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.8561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.8547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.8534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.8522e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8510e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.8460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.8448e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.8436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.8425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.8413e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.8402e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8390e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8379e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8356e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8332e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.6880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3025 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 100/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.5672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.6501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.6422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.7629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.7937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.8019e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.8019e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.7935e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.7793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.7632e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.7515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.7395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7307e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7224e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.7092e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.7020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.6961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.6921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.6879e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.6836e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.6800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.6766e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.6725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.6685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.6649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.6615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.6577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.6542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6510e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6479e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.6411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.6378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.6347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.6315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.6285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.6258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.6235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.6213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.6189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.6165e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.6142e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.6118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.6092e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.6067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.6045e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.6022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.6001e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.5980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.5962e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.5943e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.5924e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.5904e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.5885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.5866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.5846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.5826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.5807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.5787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.5768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.5750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.5733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.5715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.5697e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.5680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.5663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.5646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.5628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.5611e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.5594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.5578e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.5562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.5546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.5531e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.5516e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.5501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.5486e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.5472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.5458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.5444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.5429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.5416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.5403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.5390e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.5378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.5365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.5353e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.5351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.5348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.5345e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.5342e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.5338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.5335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.5332e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.5329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.5326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.5322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.5318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.5410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.5427e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.5443e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5519e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5558e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5571e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.7082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.3055 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 101/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 302ms/step - accuracy: 1.0000 - loss: 1.4034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.4941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.4968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.4785e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.4500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.4112e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.4072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.3999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.3979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3987e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.4006e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.4002e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.3990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.3975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.3960e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.3945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.4289e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.4588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.4856e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5775e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5901e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6014e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.6575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.6909e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.7248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.7574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.7877e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.8160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.8420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.8664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.8889e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.9096e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9290e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.1480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.3361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.5143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.6812e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.8383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.9879e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 3.1285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 3.2625e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.3887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.5087e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.6223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 3.7370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 3.9437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.1397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.3258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.5026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.6714e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.8336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 5.0049e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 5.1804e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 5.3487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 5.5123e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 5.6696e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 5.8275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.1064e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.3849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.6536e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.9113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 7.1700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 7.4432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 7.7584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 8.0712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 8.3758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 8.6826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 8.9827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.3013e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.7861e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0282e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0783e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1271e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1793e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.2310e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.2866e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.3441e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.4011e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.4602e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5226e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5846e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.6593e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.7388e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.8193e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.8988e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9824e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.0673e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1554e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.2477e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.3421e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.4376e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.5357e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6356e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.7381e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.8461e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.9577e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.0712e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.1924e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.3170e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.4462e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5771e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.7120e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.8491e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.9890e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.1298e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.2742e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.4250e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.5803e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.7372e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9999 - loss: 2.3406e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9762 - val_loss: 0.2643 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4985 Epoch 102/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9996 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9995 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - 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━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9988 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992 - val_accuracy: 0.9723 - val_loss: 0.2482 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4971 Epoch 103/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9975 - loss: 0.0067 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9976 - loss: 0.0065 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9976 - loss: 0.0063 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9978 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9978 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9978 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9978 - loss: 0.0059 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9978 - loss: 0.0059 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9978 - loss: 0.0059 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9978 - loss: 0.0059 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9978 - loss: 0.0058 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9978 - loss: 0.0058 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9979 - loss: 0.0058 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9979 - loss: 0.0058 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9979 - loss: 0.0056 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9979 - loss: 0.0056 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9979 - loss: 0.0056 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9979 - loss: 0.0056 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9979 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9980 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9980 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9980 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9980 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9989 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 - val_accuracy: 0.9761 - val_loss: 0.2387 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4982 Epoch 104/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9999 - loss: 2.1416e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9999 - loss: 2.3058e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9999 - loss: 2.4199e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9999 - loss: 2.4749e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9999 - loss: 2.5019e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9999 - loss: 2.4966e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9999 - loss: 2.4754e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9999 - loss: 2.4400e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9999 - loss: 2.3923e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9999 - loss: 2.3439e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9999 - loss: 2.2951e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9999 - loss: 2.2469e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 2.2027e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 2.1605e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 2.1206e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 2.0818e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9999 - loss: 2.0441e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.0075e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.9723e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.9380e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.9049e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.8735e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.8435e-04 - mean_absolute_error: 0.5000 - 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mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2928e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2807e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.2688e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.2573e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2459e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2349e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2240e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2135e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2031e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1930e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1831e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1734e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1639e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1546e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1454e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1365e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1277e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1191e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1106e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1023e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0942e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 299ms/step - accuracy: 1.0000 - loss: 1.0862e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.0784e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 1.0707e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 299ms/step - accuracy: 1.0000 - loss: 1.0632e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 1.0558e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 1.0485e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 299ms/step - accuracy: 1.0000 - loss: 1.0413e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 1.0343e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 1.0274e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 1.0206e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 299ms/step - accuracy: 1.0000 - loss: 1.0140e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 1.0074e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 1.0009e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 299ms/step - accuracy: 1.0000 - loss: 9.9460e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 9.8837e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 9.8223e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 299ms/step - accuracy: 1.0000 - loss: 9.7618e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 9.7023e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 9.6437e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 9.5859e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 9.5290e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 9.4729e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 9.4177e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 9.3633e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 9.3096e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 9.2568e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 9.2047e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 9.1534e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 9.1027e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 9.0528e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 9.0035e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 8.9550e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 8.9071e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 8.8598e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 8.8132e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 8.7672e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 8.7219e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 8.6771e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 8.6329e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 8.5893e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 8.5462e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 8.5037e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 8.4616e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 8.4201e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.3791e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.3386e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.2991e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 8.2601e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 3.6176e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2559 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 105/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.6963e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 2.2871e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.0522e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.8773e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.7501e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6527e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.5774e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.5145e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4599e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.4157e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3810e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3505e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3242e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3017e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2830e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2655e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2489e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2333e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2192e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2058e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1930e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1810e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1702e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1600e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1508e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.1423e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.1349e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.1277e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.1206e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.1138e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.1073e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.1010e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.0947e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.0888e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.0831e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.0777e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.0726e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.0676e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.0630e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.0584e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.0539e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0495e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0452e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0410e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0370e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0331e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0294e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0257e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0222e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.0189e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.0157e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.0125e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.0094e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.0063e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.0033e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.0003e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.9733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.9440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.9155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.8875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.8600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.8335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.8077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.7820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.7565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.7312e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.7066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.6820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.6577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 9.6340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 9.6109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 9.5914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.5721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.5532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.5348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.5163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.4979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.4795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.4613e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.4429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.4245e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.4062e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.3884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.3708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.3532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.3360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.3190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.3020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.2851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.2683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.2517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.2352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.2187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.2024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.1865e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.1708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.1554e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.1402e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.1252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.1102e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.0953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.0804e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.0658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 9.0512e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 9.0366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 9.0220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 9.0077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 8.9936e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 8.9796e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 8.9658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 8.9522e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 8.9386e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 8.9250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 8.9115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 8.8982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 8.8849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 8.8715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 8.8582e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 8.8452e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 8.8322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 7.2841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2658 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 106/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 8.8647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 1.0000 - loss: 8.1860e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 7.7723e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 7.4249e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 7.1491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 6.9120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 6.7375e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 6.5863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.4453e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.3338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 6.2535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 6.1775e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.1134e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.0649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 6.0239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 5.9837e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 5.9494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.9229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.8995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.8758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.8498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8055e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.7868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.7693e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.7534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.7394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.7239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.7084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.6928e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.6784e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.6653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.6520e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.6394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.6284e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.6170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 5.6062e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 5.5965e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 5.5876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 5.5782e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 5.5687e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 5.5589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 5.5497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 5.5403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 5.5309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 5.5218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 5.5135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 5.5051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.4972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.4898e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.4826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.4753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.4678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.4604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.4533e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.4461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.4387e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.4318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.4252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.4186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.4122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.4060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.3999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.3938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.3876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.3833e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.3791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.3748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.3703e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 5.3659e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 5.3635e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 5.3609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 5.3584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 5.3560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 5.3537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 5.3510e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 5.3482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 5.3451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 5.3423e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 5.3393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 5.3361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 5.3329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.3299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.3269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.3238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.3208e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 5.3179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 5.3149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.3118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.3087e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 5.3056e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 5.3025e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.2993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.2961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.2931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.2901e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.2873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.2845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.2818e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.2789e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.2759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.2728e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.2699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.2669e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.2637e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.2607e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.2577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.2547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.2517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.2487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.2459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.2429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.2399e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 5.2368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 5.2340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 5.2311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 5.2281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 5.2251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 5.2222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 5.2193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 4.8720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2741 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 107/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 4.1955e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 4.8708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 5.0024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 4.9469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 4.8775e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 4.7918e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 4.7436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 4.6830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 4.6235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 4.5699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 4.5303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 4.4912e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 4.4606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 4.4363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.4146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.3907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.3660e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.3718e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 4.3750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.3774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.3768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 4.3755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 4.3750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 4.3722e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 4.3708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 4.3691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 4.3688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 4.3668e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 4.3636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 4.3596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 4.3577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 4.3578e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 4.3563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 4.3546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 4.3531e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 4.3509e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 4.3491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 4.3472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 4.3451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 4.3421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 4.3385e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 4.3360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 4.3361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 4.3357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 4.3345e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 4.3333e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 4.3323e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 4.3313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 4.3301e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 4.3290e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 4.3281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 4.3266e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 4.3248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 4.3226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 4.3203e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 4.3177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 4.3148e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 4.3119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.3092e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.3063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.3034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.3006e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.2979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.2950e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.2920e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.2889e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.2856e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.2823e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.2787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.2751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.2718e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.2683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.2649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.2615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.2584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.2550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.2517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.2482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.2450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.2417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.2430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.2442e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.2455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.2466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.2475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.2484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.2493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.2500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.2506e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.2510e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.2513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.2515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.2514e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.2512e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.2512e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.2511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.2509e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.2507e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.2505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.2501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.2497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.2492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.2487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 4.2480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 4.2472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 4.2464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 4.2455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 4.2446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 4.2436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 4.2426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 4.2416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 4.2406e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 4.2395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 4.2383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 4.2372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 4.2360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 4.2348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 4.2335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 4.2322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 4.2308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 4.0683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2788 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 108/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.1629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.3116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 3.3899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 3.4658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 3.4695e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.4563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.4496e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.5199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.5521e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.5716e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.5882e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.6027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.6143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.6287e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.6404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.6489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.6531e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.6551e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.6711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.6817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.6881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.6938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.6991e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.7024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.7046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 3.7066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 3.7081e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 3.7094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.7095e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.7084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.7076e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.7060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.7035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.7015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.6997e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.6969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.6938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.6912e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.6888e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.6857e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.6820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.6779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.6742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.6705e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.6665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.6628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.6595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.6613e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.6627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.6640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.6650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.6658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.6663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.6666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.6667e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.6664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.6657e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.6648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.6640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.6630e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.6618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.6608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.6599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.6587e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.6573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.6558e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.6543e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.6526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.6508e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.6490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.6474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.6457e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.6439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.6424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.6410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.6396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.6379e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.6362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.6344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.6326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.6307e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.6290e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.6273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.6256e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.6238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.6221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.6204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.6186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.6168e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.6149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.6130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.6111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.6090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.6069e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.6048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.6026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.6005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.5983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.5961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.5939e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.5916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.5893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.5869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.5845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.5821e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.5797e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.5774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.5750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.5727e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5704e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5657e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.5609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.5585e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.5561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.5536e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.5512e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.5487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.5462e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 3.2515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2838 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 109/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 294ms/step - accuracy: 1.0000 - loss: 2.7159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 2.8299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.8475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.8003e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.7418e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.6991e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 2.6740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 2.6478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.6401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.6347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.6363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 2.6486e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 2.6600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 2.6699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.6782e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.6826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.6838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.6834e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.6828e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.6817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.6789e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.6765e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.6750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.6728e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.6708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.6693e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.6685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.6670e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.6685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.6692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.6699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.6701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.6693e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.6687e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.6641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.6635e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.6629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.6621e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.6612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.6602e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.6593e-06 - 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0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.6145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.6135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6125e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6114e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6103e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.6095e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.6068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6059e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6049e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.6039e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6013e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.6008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.6002e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.5996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.5990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.5983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.5976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.5969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.5962e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.5109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2892 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 110/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 2.6970e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 2.6051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 2.5636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 2.5066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.4515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.4656e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.4703e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.4592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.4382e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.4181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 2.4069e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 2.4529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 2.4902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 2.5181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 2.5396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 2.5530e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 2.5615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 2.5662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.5699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.5726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.5726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.5715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.5711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.5696e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.5677e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.5655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.5638e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.5613e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 2.5580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.5541e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.5502e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.5464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.5420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.5378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 2.5342e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 2.5307e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 2.5278e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 2.5251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 2.5230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 2.5204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 2.5176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 2.5145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 2.5114e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 2.5081e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 2.5044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 2.5009e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 2.4976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 2.4941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 2.4906e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.4872e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.4839e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.4805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.4769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.4734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.4699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.4663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.4626e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.4590e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.4556e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.4524e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.4498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.4473e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.4449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.4424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.4398e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.4374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.4352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.4330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.4306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.4283e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.4260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.4236e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.4213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.4191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.4169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.4146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.4123e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.4099e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.4077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.4054e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.4032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.4010e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.3989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.3968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.3946e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.3925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.3905e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.3885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.3865e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.3845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.3825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.3805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.3796e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.3788e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.3779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.3771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.3764e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.3759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.3753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.3746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.3739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.3732e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.3724e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.3716e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.3708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.3699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.3690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.3681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.3672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.3663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.3654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.3645e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.3635e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.3625e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.3615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.3605e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.3594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.3583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.3572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.3562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 2.2301e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2938 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 111/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.7024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.8036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.8467e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.8503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.8346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.8182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.8491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.8646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.8673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.8686e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.8704e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.8735e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.8765e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.8817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.8866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.8894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.8905e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.8905e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.8904e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.8895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.8870e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.8846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.8835e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.8762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.8742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.8718e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.8695e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.8677e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.8657e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.8638e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.8623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.8612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.8600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.8585e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.8574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.8562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.8550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.8535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8522e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8496e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.8488e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.8480e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8144e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8136e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.8128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.8120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.8113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.8105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.8097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.8090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.8083e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.8075e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.8067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.8058e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.8050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.8041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.8037e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.8034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.8031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.8028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.8025e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8042e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8049e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8054e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8065e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8070e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8074e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.8615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2991 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 112/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.6821e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.7222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.7371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.7312e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.7119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6986e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.6956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.6983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.6989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7013e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.7158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.7188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.7193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.7202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.7221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.7228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.7223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.7219e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.7221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.7221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.7225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.7230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.7234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.7233e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.7227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.7218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.7236e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.7247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.7252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.7256e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.7262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.7265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.7265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.7266e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.7268e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.7265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.7260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.7254e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.7248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.7239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.7228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.7216e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 301ms/step - accuracy: 1.0000 - loss: 1.7206e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 301ms/step - accuracy: 1.0000 - loss: 1.7196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 301ms/step - accuracy: 1.0000 - loss: 1.7186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 21s 301ms/step - accuracy: 1.0000 - loss: 1.7178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 301ms/step - accuracy: 1.0000 - loss: 1.7171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 301ms/step - accuracy: 1.0000 - loss: 1.7164e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 301ms/step - accuracy: 1.0000 - loss: 1.7155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 301ms/step - accuracy: 1.0000 - loss: 1.7146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 301ms/step - accuracy: 1.0000 - loss: 1.7138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 300ms/step - accuracy: 1.0000 - loss: 1.7129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 300ms/step - accuracy: 1.0000 - loss: 1.7119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 300ms/step - accuracy: 1.0000 - loss: 1.7110e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 300ms/step - accuracy: 1.0000 - loss: 1.7102e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 18s 300ms/step - accuracy: 1.0000 - loss: 1.7093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 300ms/step - accuracy: 1.0000 - loss: 1.7083e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 300ms/step - accuracy: 1.0000 - loss: 1.7075e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 300ms/step - accuracy: 1.0000 - loss: 1.7069e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 300ms/step - accuracy: 1.0000 - loss: 1.7063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 300ms/step - accuracy: 1.0000 - loss: 1.7058e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 300ms/step - accuracy: 1.0000 - loss: 1.7051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 300ms/step - accuracy: 1.0000 - loss: 1.7045e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 300ms/step - accuracy: 1.0000 - loss: 1.7038e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 300ms/step - accuracy: 1.0000 - loss: 1.7029e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 300ms/step - accuracy: 1.0000 - loss: 1.7020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 300ms/step - accuracy: 1.0000 - loss: 1.7012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 300ms/step - accuracy: 1.0000 - loss: 1.7003e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 300ms/step - accuracy: 1.0000 - loss: 1.6996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 300ms/step - accuracy: 1.0000 - loss: 1.6988e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 300ms/step - accuracy: 1.0000 - loss: 1.6980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 300ms/step - accuracy: 1.0000 - loss: 1.6973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 300ms/step - accuracy: 1.0000 - loss: 1.6965e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 300ms/step - accuracy: 1.0000 - loss: 1.6957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 300ms/step - accuracy: 1.0000 - loss: 1.6948e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 300ms/step - accuracy: 1.0000 - loss: 1.6939e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 300ms/step - accuracy: 1.0000 - loss: 1.6929e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 300ms/step - accuracy: 1.0000 - loss: 1.6921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 300ms/step - accuracy: 1.0000 - loss: 1.6914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 300ms/step - accuracy: 1.0000 - loss: 1.6906e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 300ms/step - accuracy: 1.0000 - loss: 1.6899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 300ms/step - accuracy: 1.0000 - loss: 1.6891e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 300ms/step - accuracy: 1.0000 - loss: 1.6884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 300ms/step - accuracy: 1.0000 - loss: 1.6877e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 300ms/step - accuracy: 1.0000 - loss: 1.6869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 300ms/step - accuracy: 1.0000 - loss: 1.6861e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 300ms/step - accuracy: 1.0000 - loss: 1.6854e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 300ms/step - accuracy: 1.0000 - loss: 1.6845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 300ms/step - accuracy: 1.0000 - loss: 1.6837e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 300ms/step - accuracy: 1.0000 - loss: 1.6828e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 300ms/step - accuracy: 1.0000 - loss: 1.6820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 1.6813e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 300ms/step - accuracy: 1.0000 - loss: 1.6807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 1.6800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 300ms/step - accuracy: 1.0000 - loss: 1.6795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 300ms/step - accuracy: 1.0000 - loss: 1.6788e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 300ms/step - accuracy: 1.0000 - loss: 1.6783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 300ms/step - accuracy: 1.0000 - loss: 1.6777e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.6771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 1.6766e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 1.6760e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 1.6754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 1.6748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 1.6742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 1.6736e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.6730e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.6725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.6719e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.6713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.6707e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.6701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.6695e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.6688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.6681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.6675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.6668e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 1.5896e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3024 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 113/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.5160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.4679e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.4679e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.4478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.4222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.4044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.3940e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.3826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.3692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.3528e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.3478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.3436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3409e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3382e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.3356e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.3328e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.3304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.3275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.3239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.3210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.3141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.3136e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.3128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.3118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.3111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.3113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.3113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.3117e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.3122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.3126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.3130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.3138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.3146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.3152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.3160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.3169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.3179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.3188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.3196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.3204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.3213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.3220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.3228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.3235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.3246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.3255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.3262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.3269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.3276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.3303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.3328e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.3352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.3374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.3395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.3414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.3433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.3451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.3468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.3484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.3498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.3511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.3533e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.3554e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.3574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.3593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.3611e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.3628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.3644e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.3666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.3704e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.3740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.3774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.3807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.3953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.3979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.4004e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.4028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.4051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.4073e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 1.4093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 1.4113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 1.4132e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 299ms/step - accuracy: 1.0000 - loss: 1.4149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 1.4167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 1.4184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 299ms/step - accuracy: 1.0000 - loss: 1.4200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 1.4215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 1.4231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 299ms/step - accuracy: 1.0000 - loss: 1.4245e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.4259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.4272e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.4285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.4296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.4308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.4318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.4328e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.4339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.4349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.4359e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.4368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.4377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.4386e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.4394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.4402e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.4410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.4417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.4423e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.4429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.4435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.4441e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.5116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3056 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 114/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.2794e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.3415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3659e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3509e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3792e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.3868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.3872e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.3876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.3878e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.3891e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.3894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.3856e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.3827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.3802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.3780e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.3750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.3720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.3695e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.3666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.3643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.3621e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.3603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.3601e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.3596e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.3589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.3583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.3577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.3566e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.3560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.3555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.3548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.3544e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.3543e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.3542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.3548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.3550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.3551e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.3552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.3550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.3547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.3542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.3538e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.3532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.3526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.3521e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.3517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.3513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.3507e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.3500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.3494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.3486e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.3478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.3470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.3464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.3456e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.3449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.3442e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.3436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.3430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.3425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.3418e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.3412e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.3406e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.3399e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.3391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.3384e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.3376e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.3370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.3364e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.3358e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.3352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.3345e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.3338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.3331e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.3323e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.3315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.3307e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3283e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3243e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3201e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.3185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.3178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.3170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.3163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.3155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.3147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.3140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.3132e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.3124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.3116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.3109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.3101e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.3094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.3086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.3079e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.3073e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.3066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.3060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.3053e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.3047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.3040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.3033e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.3027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.3020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.2231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3089 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 115/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.0807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.1450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1607e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.1788e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.1729e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.1753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.1752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1723e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.1699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.1686e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.1650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1611e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1605e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1543e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1524e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1353e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1293e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1277e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1268e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1261e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.1245e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.1238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.1232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.1226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.1218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.1209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.1200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.1191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.1182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.1173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1157e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1142e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1101e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1085e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1101e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1107e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1114e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1127e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1132e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1144e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1156e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1168e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.0986e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3114 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 116/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 9.3159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.0022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.0242e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.0259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0321e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.0316e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.0301e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.0306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0287e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.0265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.0252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.0311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0496e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0507e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.0527e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.0526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.0523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.0517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.0513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.0505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0495e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0473e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.0463e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.0461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.0467e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.0472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.0476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.0477e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.0479e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.0482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.0485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.0488e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.0490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.0492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.0493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.0493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.0491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.0490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.0489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.0491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.0492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.0494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.0496e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.0498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.0499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.0500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.0501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.0501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.0500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.0499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.0499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.0498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0496e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0495e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.0493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.0493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.0492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.0490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.0489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.0487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0483e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0481e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0479e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.0476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.0474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.0472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.0470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.0467e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.0465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.0466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.0466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.0466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.0466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.0466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.0466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.0466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.0465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.0465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.0465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0502e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0520e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.0537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0569e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.0583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.0626e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.0678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.0712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0723e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0743e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.1908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3143 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 117/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.0516e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.0531e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.0514e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.0313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.0094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 9.9896e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 9.9152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 9.8315e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 9.7293e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 9.6518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 9.6135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 9.5785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.5593e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.5571e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.6068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.6356e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.6555e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.6705e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.6808e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.6915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.6988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.7057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.7140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.7226e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.7294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.7372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.7423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.7431e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.7409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.7367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.7321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.7353e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.7367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.7367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.7379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.7366e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.7345e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.7321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.7303e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.7269e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.7228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.7176e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.7136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.7082e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.7013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.6949e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.6896e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.6833e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.6770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.6716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.6668e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.6622e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.6578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.6557e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.6538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.6510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.6472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.6434e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.6402e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.6366e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.6341e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.6317e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.6291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.6268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.6239e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.6206e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.6175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.6144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.6105e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.6067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.6032e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.5993e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.5956e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.5920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.5883e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.5850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.5813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.5776e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.5740e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.5703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.5665e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.5628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.5591e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.5553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.5517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.5482e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.5449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.5414e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.5377e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.5339e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.5300e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.5258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.5215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.5172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.5132e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.5091e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.5053e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.5017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.4983e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.4950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.4919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.4888e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.4858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.4826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.4792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.4757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.4723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.4692e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.4660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.4629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.4598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.4567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.4536e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.4504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.4473e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.4440e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.4406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.4372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.4340e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.4306e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 9.0292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3173 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 118/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.6335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 2.9604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 2.5875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.3257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.1329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.9875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.8802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.7942e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.7184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.5604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.5211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.4896e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.4612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.4346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.4094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.3865e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.3657e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.3465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.3288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.3124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.2976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.2836e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.2704e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.2731e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.2751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.2769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.2778e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.2783e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.2523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.2400e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.2375e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.1591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.1574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.1557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.1541e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.1524e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.1508e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.1492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.1476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.1460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.1445e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.1429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.1414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.1399e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.1384e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.1369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.1354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.1344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.1334e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.1324e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.1313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.1303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.1293e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.1282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1272e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.1251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 9.9136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3190 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 119/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 8.8208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 9.3213e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 9.3935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.2448e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.0734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 8.8976e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 8.8680e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.8075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.7107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.6322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.5792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 8.5272e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 8.4852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 8.4701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 8.4646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 8.4502e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.4281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.4042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 8.3825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.3582e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 8.3339e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 8.3115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 8.2936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 8.2743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.2558e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.2385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.2229e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.2081e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 8.1933e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 8.1814e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 8.1686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.1560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.1419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.1283e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.1167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.1050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.0944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.0846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.0751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.1721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.2604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 8.3429e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 8.4199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 8.4901e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 8.5614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 8.6285e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 8.6917e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 8.7497e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 8.8038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 8.8548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 8.9026e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 8.9471e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 8.9885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 9.0271e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 9.0782e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 9.1265e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 9.1713e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 9.2138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 9.2539e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 9.2924e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 9.3287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 9.3632e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 9.3961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 9.4268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 9.4553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 9.4817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 9.5065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 9.5295e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 9.5507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 9.5722e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 9.5929e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 9.6124e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.6311e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.6492e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.6664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.6822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.6972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.7113e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.7248e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.7374e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.7489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.7599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.7710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.7815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.7915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.8010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.8107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.8198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.8284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.8362e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.8437e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.8505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.8566e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.8623e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.8677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.8725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.8770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.8813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.8852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.8886e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.8915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.8942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.8969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 9.8992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 9.9009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 9.9024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 9.9038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 9.9048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 9.9057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.9064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.9070e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.9071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.9070e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 9.9065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 9.9059e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 9.9050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 9.9038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 9.9024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 9.9010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 9.8993e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 9.7008e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3214 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 120/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 7.5397e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.1430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.2983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.2802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 2.2036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.1189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.0400e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.9671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.9004e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.8396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.7871e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.7407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.7000e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.6633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.5745e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.5501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.5280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.5072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.4876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.4689e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.4517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 1.0000 - loss: 1.4353e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 1.0000 - loss: 1.4198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.4054e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.3917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.3787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.3662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.3545e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.3433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.3325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.3219e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.3126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.3036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.2950e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.2867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.2785e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.2707e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.2631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.2557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.2485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.2416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.2348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.2280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.2216e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.2155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.2094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.2036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.1979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.1925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 1.1888e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.1852e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.1816e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 1.1781e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 1.1747e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 1.1711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 1.1677e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 1.1643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 1.1610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 1.1578e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 1.1548e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 1.1518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 1.1488e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 1.1458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.1429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.1400e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.1372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.1343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.1315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.1288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.1262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.1235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.1210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.1185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.1160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.1135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.1111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.1087e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.1063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.1040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.1017e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.0995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.0973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.0951e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.0931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.0910e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.0890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 1.0869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.0849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.0829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.0810e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.0790e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.0771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.0752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.0733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.0715e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.0696e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.0678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.0660e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.0642e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.0624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 1.0606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.0589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.0571e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.0554e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.0537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.0520e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.0503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.0486e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.0470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.0454e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.0438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 1.0422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 1.0407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 1.0391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.0375e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.0360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.0345e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.0330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 8.5313e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3215 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 121/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.0315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 9.6499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 9.2573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 9.0153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 8.7713e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 8.5958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 8.5011e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 8.3753e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.2535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.1461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.0779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.0098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 7.9534e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.9119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.8765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.8379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.8018e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.7644e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.7323e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.7092e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.6873e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.6683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.6524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.6413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.6302e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.6197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.6108e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.6024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.5927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.5829e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.5779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.5718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.5639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.5643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.5645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.5626e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.5599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.5574e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.5544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 7.5501e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 7.5445e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 7.5416e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 7.5392e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 7.5357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 7.5324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 7.5288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 7.5260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 7.5228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 7.5194e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 7.5163e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 7.5136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 7.5109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.5075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.5034e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.4996e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.4954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.4905e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.4854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.4811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.4763e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.4733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 7.4701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.4668e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.4638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.4605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.4569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.4540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.4506e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.4467e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.4430e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.4398e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.4369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.4338e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.4308e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.4278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.4245e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.4208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.4170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.4131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.4090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.4044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.3998e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.3954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.3908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.3862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.3842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.3822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.3804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.3782e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.3758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.3733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.3707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.3678e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.3650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.3623e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.3594e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.3564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.3534e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.3504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.3472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.3438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.3406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.3383e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.3358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.3332e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.3305e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.3278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.3251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.3223e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.3197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.3172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.3152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.3133e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.3111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.3089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.3065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.3039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.3014e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.2989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.2972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 7.0892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3249 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 122/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 6.3166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 6.3453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.2598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.1310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.0689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.9964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.9865e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.9585e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.9337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.9211e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.9190e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.9143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.9088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.9126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.9186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.9193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.9150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.9073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.9032e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.8978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.8891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.8804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.8771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.8731e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.8732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.8734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.8746e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.8743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.8814e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.8861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.8920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.8954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.8971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.8988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.9009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.9039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.9072e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.9103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.9126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.9138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.9143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.9143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.9153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.9165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.9173e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.9185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.9202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.9212e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.9224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 5.9332e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 5.9438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 5.9536e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 5.9624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 5.9700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 5.9771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 5.9834e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 5.9889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 5.9947e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.0004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.0054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.0105e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.0154e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.0199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.0240e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.0273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.0301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.0331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.0360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.0386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.0411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.0439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.0464e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.0485e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.0505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.0524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.0541e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.0554e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.0565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.0576e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.0585e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.0589e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.0593e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.0596e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.0597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.0598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.0598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.0599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.0599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.0599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.0597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.0594e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.0590e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.0584e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.0579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.0576e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.0572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.0568e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.0563e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.0562e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0555e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0549e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.0533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.0524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.0514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.0504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.0494e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.0484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.0474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.0463e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.0451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.0438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.0425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.0413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.0412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.0409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.0406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.0408e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.0409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 6.0507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3287 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 123/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 4.9956e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 5.3494e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 5.6335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 5.7075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 5.6923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 5.6969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 5.7120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 5.7239e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.7882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.8366e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.8799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.8995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.9117e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.9207e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.9288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.9323e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.9291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.9218e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.9139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.9023e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.8883e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8678e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8593e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8522e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.8451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.8377e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.8336e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.8282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.8212e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.8166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.8136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.8087e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.8030e-07 - 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0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.2216e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.2381e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.2540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.2693e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.2838e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.2980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.3116e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.3248e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.3376e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.3500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.3620e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.3737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.3851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.3960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.4068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.4173e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.4272e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.4373e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.4468e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.4559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.4648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.4734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.4816e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 8.4551e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3288 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 124/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 7.0126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 6.7886e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 6.6492e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.5834e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.4507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.3252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 6.2583e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.1822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.1273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.0876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.0755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.0574e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.0568e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.0563e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.0553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.0481e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.0352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.0195e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.0124e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.0020e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.9879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.9787e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.9723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.9677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.9632e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.9598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.9564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.9528e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.9484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.9431e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.9381e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.9324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.9244e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.9165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.9098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.9040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.8981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.8940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.8899e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.8846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.8785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.8724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.8663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.8599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.8535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.8474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.8420e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.8365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.8309e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.8257e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.8206e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.8155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 5.8001e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.7954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.7904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.7859e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.7821e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 5.7782e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 5.7750e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 5.7720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 5.7693e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 5.7666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 5.7638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.7608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.7580e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.7548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.7513e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.7477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.7445e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.7412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.7379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.7358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.7341e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.7322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.7300e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.7277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.7254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.7229e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.7203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.7177e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.7152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.7127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.7103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 5.7084e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 5.7065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 5.7045e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 5.7023e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 5.6999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 5.6975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 5.6952e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.6927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.6901e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.6877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 5.6851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 5.6826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.6801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.6777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.6754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.6729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.6704e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.6680e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.6655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.6628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.6601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.6575e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.6549e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.6524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.6500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.6490e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.6480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.6469e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.6460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.6451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.6442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.6432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.6421e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.6411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.6400e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 5.5128e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3322 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 125/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.6386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 5.5627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.7062e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.6097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.6163e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.6060e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.6052e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.5985e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.5620e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.5432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.5343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.5207e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.5129e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.5035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.5056e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.4999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.4924e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.4837e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.4742e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.4610e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.4484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.4369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.4272e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 5.9738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 5.9804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 5.9866e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.9923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.9978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.0029e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.0075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.0119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.0161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.0200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.0238e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.0273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.0306e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0338e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0396e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.0453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.0477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.0500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.0522e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.0542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.0564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.0585e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.0605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.0624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.0640e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.0655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.0669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.0682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.0693e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.0703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.0714e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.0723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 6.1754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3325 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 126/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 4.5349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 4.8205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.9325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.9295e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.8739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.8199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.7822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.7572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.7244e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.7033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.7287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.7411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.7520e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.7648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.7729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.7854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.7919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.7968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.8006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 4.8022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 4.8012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 4.8000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 4.8006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 4.8063e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 4.8108e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 4.8149e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 4.8194e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.8227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.8243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.8252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.8258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.8256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.8252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.8250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.8274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.8295e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.8322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.8349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.8372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.8401e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.8441e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.8472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.8502e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.8524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.8536e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.8546e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.8565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.8578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.8599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.8622e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.8646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.8663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.8674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.8683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.8691e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.8697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.8697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.8696e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.8700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.8699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.8703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.8707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.8709e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.8732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.8752e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.8768e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.8783e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.8794e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.8799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.8803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.8808e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.8810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.8812e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.8813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.8812e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.8810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.8806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.8816e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.8825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.8833e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.8839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.8844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.8850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.8853e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.8856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.8858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.8861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.8863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.8863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.8864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.8864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.8864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.8862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.8858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.8856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.8851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.8846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.8841e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.8836e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.8830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.8825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.8819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.8812e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 4.8804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 4.8796e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 4.8787e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 4.8780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 4.8773e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 4.8764e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 4.8756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 4.8747e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 4.8737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 4.8726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 4.8713e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 4.8701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 4.8689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 4.8675e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 4.8661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 4.8648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 4.8634e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 4.6986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3366 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 127/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 5.4200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 5.1037e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 5.0194e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.9144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 4.7883e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.6846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.6075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.5601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.5066e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.4626e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.4392e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.4127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.3858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.3648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.3489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.3391e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3147e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.2992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.2932e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.2879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.2818e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.2770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.2722e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.2663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.2606e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.2567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.2608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.2633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.2664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.2695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.2728e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.2751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.2775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.2802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.2824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.2839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.2846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.2852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.2851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.2843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.2836e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.2831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.2826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.2823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.2837e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.2848e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.2857e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2865e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2871e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2886e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2896e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2930e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2939e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2945e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.2951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.2964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.2971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.2978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.2985e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.2990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.2995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.2999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.3002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.3004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.3002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.2999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.2997e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 4.2995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 4.2991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 4.2987e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 4.2984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.2980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.2977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.2974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.2971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.2967e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.2964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.2959e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.2958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.2954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.2950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.2944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.2939e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.2934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.2929e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.2925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.2921e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.2916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.2911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.2905e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.2899e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.2892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.2884e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.2877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.2869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.2860e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.2852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.2845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.2838e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.2833e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.2830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.2828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.2824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.2822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.2819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.2816e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.2813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.2810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 4.2375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3398 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 128/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 4.2739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 4.4268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 4.3832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 4.2889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 4.2064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 4.1337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 4.0896e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 4.0535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 4.0121e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.9731e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.9556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 3.9347e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 3.9180e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 3.9043e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 3.9000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 3.9119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 3.9233e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 3.9301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 3.9373e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 3.9432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 3.9449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.9444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.9445e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.9425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 3.9477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 3.9521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 3.9573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 3.9632e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 3.9695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 3.9740e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 3.9775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.9804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.9817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.9819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.9825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.9824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.9816e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.9809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 3.9800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 3.9784e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 3.9763e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 3.9744e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 3.9729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 3.9708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 3.9682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.9656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.9633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.9607e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.9587e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.9567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.9548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.9524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.9499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.9472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.9450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.9430e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.9408e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.9389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.9372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.9352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.9335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.9319e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.9302e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.9284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.9266e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.9248e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.9230e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.9212e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 3.9192e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 3.9171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 3.9155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 3.9139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 3.9123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 3.9106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 3.9089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.9073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.9055e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.9038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.9021e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 3.9005e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 3.8986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 3.8969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.8952e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.8934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.8915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.8897e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.8879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.8862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.8844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.8826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.8809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.8792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.8776e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.8759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.8744e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.8729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.8715e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.8702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.8688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.8674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.8659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.8650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.8641e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 3.8632e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.8621e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 3.8612e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.8603e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 3.8595e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 3.8587e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.8582e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.8578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.8573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.8567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 3.8560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 3.8554e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 3.8547e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 3.8541e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 3.8535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 3.8529e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 3.8521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 3.7662e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3431 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 129/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 3.9612e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.7088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.6137e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.7411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.7454e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.7268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 3.7801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.8009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.7982e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.7939e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.7964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 3.7923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 3.8103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 3.8260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.8371e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.8411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.8391e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.8367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.8329e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.8262e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.8164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.8074e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.8005e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.7945e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.7905e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 1.0000 - loss: 3.7875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 1.0000 - loss: 3.7851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 1.0000 - loss: 3.7840e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 1.0000 - loss: 3.7815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 1.0000 - loss: 3.7790e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 1.0000 - loss: 3.7771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 1.0000 - loss: 3.7755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 1.0000 - loss: 3.7734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 3.7711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 1.0000 - loss: 3.7692e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 1.0000 - loss: 3.7664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 1.0000 - loss: 3.7634e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 1.0000 - loss: 3.7602e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 1.0000 - loss: 3.7569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 1.0000 - loss: 3.7552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 1.0000 - loss: 3.7538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 1.0000 - loss: 3.7519e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 1.0000 - loss: 3.7498e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 1.0000 - loss: 3.7474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 1.0000 - loss: 3.7446e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 1.0000 - loss: 3.7426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 1.0000 - loss: 3.7409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 1.0000 - loss: 3.7391e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 1.0000 - loss: 3.7379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 1.0000 - loss: 3.7370e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 3.7359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 3.7349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 3.7335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 3.7322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 3.7310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 3.7301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 3.7288e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 3.7145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 3.7127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 3.7109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 3.7090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 3.7068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 3.7048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 3.7029e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 3.7008e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 3.6988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 3.6970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 3.6958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.6944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.6929e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.6912e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.6895e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 3.6878e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 3.6861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 3.6843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.6825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.6807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.6809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.6810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.6813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.6815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.6816e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.6815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.6827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.6837e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.6846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.6855e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.6862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.6868e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.6873e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.6878e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.6881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.6884e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.6885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.6885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.6885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 3.6884e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 3.6888e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.6891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.6896e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.6900e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.6903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.6906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.6908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.6912e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.6915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.6918e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.6921e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.6923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.6925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.6926e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.6928e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.6928e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 3.6963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3462 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 130/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.4377e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.8277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.8423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.8285e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.7614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.6837e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.6419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.5942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.5528e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.5241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.5061e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.4847e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.4649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.4565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.4511e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.4470e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.4395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.4307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.4222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.4151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.4127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.4103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.4080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.4040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.4016e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.3987e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.4165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.4316e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.4446e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.5758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.6940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 3.8002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.8960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 3.9831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.0625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.1348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.2008e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.2618e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.3183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.3719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.4221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.7801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.1131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.4228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.8358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.2211e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.5818e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.9356e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 7.2673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 7.5790e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 7.8720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.1473e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 8.4056e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 8.7139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.0042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.2777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.5364e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.7815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.0035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.0918e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.3327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.4152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5216e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.7668e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.0028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.3002e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.5999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.8983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.2982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.7786e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.2867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.8654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 5.4534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.2110e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 7.1887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 8.4091e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.9451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2421e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.5330e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.8863e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.3841e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.9512e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.6178e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.4115e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.2770e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 6.2129e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 7.2400e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.3458e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.5317e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0780e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2110e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3540e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.5075e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9999 - loss: 1.6670e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9999 - loss: 1.8375e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9999 - loss: 2.0186e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9999 - loss: 2.2099e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9999 - loss: 2.4040e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9999 - loss: 2.6050e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9999 - loss: 2.8129e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9999 - loss: 3.0285e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9999 - loss: 3.2465e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9999 - loss: 3.4679e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9999 - loss: 3.6965e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9999 - loss: 3.9285e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9999 - loss: 4.1660e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9999 - loss: 4.4083e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9998 - loss: 4.6550e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9998 - loss: 4.9027e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9998 - loss: 5.1495e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9998 - loss: 5.3970e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9998 - loss: 5.6464e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9998 - loss: 5.8954e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9998 - loss: 6.1418e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9998 - loss: 6.3864e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9998 - loss: 6.6312e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9998 - loss: 6.8754e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9998 - loss: 7.1171e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 - val_accuracy: 0.9705 - val_loss: 0.2165 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4957 Epoch 131/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9969 - loss: 0.0081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9970 - loss: 0.0079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4975  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9971 - loss: 0.0076 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4976  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9973 - loss: 0.0073 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9974 - loss: 0.0070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4977  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9975 - loss: 0.0068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9975 - loss: 0.0066 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4978  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9976 - loss: 0.0064 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9977 - loss: 0.0062 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4979  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9977 - loss: 0.0061 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9978 - loss: 0.0060 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4980  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9978 - loss: 0.0059 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9979 - loss: 0.0058 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9979 - loss: 0.0057 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4981  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9979 - loss: 0.0056 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9980 - loss: 0.0055 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9980 - loss: 0.0054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9980 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4982  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9981 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9981 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9982 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4983  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4984  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9985 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9985 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9988 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9988 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9989 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 - val_accuracy: 0.9746 - val_loss: 0.2460 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4978 Epoch 132/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9994 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9994 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9994 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9994 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - 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━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - 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━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - 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━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9995 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9996 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4996 - val_accuracy: 0.9765 - val_loss: 0.2439 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4984 Epoch 133/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 7.8935e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 7.8588e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.6873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 7.4218e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 7.1493e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 6.9189e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 6.7245e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 6.5736e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.4301e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.3214e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 6.2439e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 6.2115e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 6.1853e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 6.1601e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 6.1365e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.1055e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.0681e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.0283e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.9861e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.9402e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.8918e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8460e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8003e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.7536e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.7069e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.6606e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.6146e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.5683e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.5240e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.4799e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 5.4361e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 5.3929e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 5.3499e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 5.3076e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 5.2669e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 5.2267e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 5.1873e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.1487e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.1110e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.0736e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.0368e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 5.0005e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.9649e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.9298e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.8952e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.8613e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.8280e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.7953e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.7632e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.7317e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.7009e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.6705e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.6405e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.6111e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.5821e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.5536e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.5256e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.4979e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.4708e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.4442e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.4180e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 4.3923e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.3670e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.3421e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 4.3175e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.2933e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.2695e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.2460e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 4.2228e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.2000e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.1776e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 4.1554e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.1337e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.1122e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.0912e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.0705e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.0501e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.0300e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.0102e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.9906e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.9713e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.9522e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.9335e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.9150e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.8968e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.8788e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.8611e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.8436e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.8264e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.8093e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.7925e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.7759e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.7595e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.7433e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.7273e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.7115e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.6959e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.6804e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.6652e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.6502e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.6353e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.6206e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.6060e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.5916e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.5774e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.5634e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.5495e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.5357e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.5221e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.5087e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.4955e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.4824e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.4694e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.4565e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.4438e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.4313e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.4188e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.4065e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.3943e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.3822e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 1.9461e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9768 - val_loss: 0.2586 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 134/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 9.5660e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 9.4919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 9.4807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 9.5202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 9.4625e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 9.3672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 9.2633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 9.1573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 9.0587e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.9835e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 8.9352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 8.8868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 8.8484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 8.8188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 8.7955e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.7679e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.7369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.7115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.6854e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.6595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.6324e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.6061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.5846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.5615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.5446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.5299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.5159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.4998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.4827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.4648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.4464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.4294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.4110e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.9002e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.8915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.8829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.8745e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.8665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.8584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.8502e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.8420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.8339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.8258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.8175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.8093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.8012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.7930e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.7849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.7769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.7690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.7610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.7530e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.7449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.7368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.7286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.7204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.7122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.7041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.6961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.6881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.6802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.6725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.6646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.6567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.6489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.6410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.6331e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.6252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.6172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.6094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.6015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 6.6664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2673 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 135/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 5.7106e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.6834e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.7519e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.0727e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.1457e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.1503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.1292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.2839e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.3604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.4044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.4340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.4447e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.4504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.4514e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.4494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.4369e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.4211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.4019e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.3828e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.4553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.5116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.5577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.5969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.6304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.6613e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.6873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.7095e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.7268e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.7395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.7492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.7557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.7595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.7668e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.7719e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.7761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.7779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.7787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.7788e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.7781e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.7757e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.7722e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.7676e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.7623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.7563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.7493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.7420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.7344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.7263e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.7186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.7107e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.7030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.6950e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.6865e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.6776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.6684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.6590e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.6492e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.6394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.6296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.6205e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.6115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.6027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.5941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.5852e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.5761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.5713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.5663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.5610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.5553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.5497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.5440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.5381e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.5322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.5262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.5202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.5140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.5076e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.5024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.4970e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.4916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.4861e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.4805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.4750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.4693e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.4636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.4579e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.4529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.4477e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.4425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.4371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.4317e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.4264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.4210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.4155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.4101e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.4046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.3991e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.3936e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.3882e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.3827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.3770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.3714e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.3658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.3601e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.3543e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.3486e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.3429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.3371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.3315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.3258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.3203e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.3147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.3090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.3033e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.2978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.2922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.2865e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.2809e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.2753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.2697e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 5.6024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2722 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 136/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 4.2589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 4.4066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.4640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.3995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.3351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.2916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.2608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.2251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.1841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.1586e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.1430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.1252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.1142e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.1220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.1328e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.1394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.1433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 4.1455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.1468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.1457e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.1419e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.1387e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.1363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.1335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.1309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.1294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.1282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.1262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.1239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.1216e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 4.1192e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 4.1177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.1154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.1128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.1105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.1078e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.1052e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.1028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.1007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.0980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.0953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.0922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.0894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.0864e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.0831e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.0799e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.0770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.0738e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.0706e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.0677e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.0649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.0620e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.0589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.0568e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.0547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.0526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.0503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.0480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.0459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.0435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.0413e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.0392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.0372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.0349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.0325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.0302e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.0280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.0256e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.0231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.0206e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.0183e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.0159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.0137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.0115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.0093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.0071e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.0047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.0023e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.9998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.9973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.9946e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.9920e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.9895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.9869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.9844e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.9819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.9795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.9770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.9744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.9718e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.9692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.9665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.9637e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.9610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.9584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.9557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.9530e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.9503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.9477e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.9450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.9423e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.9396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.9370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.9344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.9321e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.9299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.9279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.9259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.9239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.9220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.9200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.9180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.9159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.9139e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.9118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.9100e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.9082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.9063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.9046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.9027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 3.6862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2788 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 137/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 3.3934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.6098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.6723e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 3.6035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 3.5521e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.5795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.6128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.6138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 3.5980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 3.5793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.5649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.5454e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.5327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.5232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.5152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.4974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.4885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.4796e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.4693e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.4576e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 3.4466e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.4367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.4265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.4177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.4102e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.4044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.3979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.3909e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.3840e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.3768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.3691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.3610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.3534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.3463e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.3389e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.3319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.3255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.3195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.3135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.3075e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.3016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.2958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.2899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.2841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.2785e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.2734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.2685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.2644e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.2610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.2577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.2542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.2507e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.2472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.2437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.2403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.2366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.2330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.2295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.2260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.2225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.2193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.2162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.2142e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.2122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.2102e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.2082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.2062e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.2041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.2020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.2000e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.1980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.1960e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.1940e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.1921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.1902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.1881e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.1862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.1842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.1822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.1801e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.1780e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.1760e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.1740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.1720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.1701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.1681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.1662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.1641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.1620e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.1599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.1578e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.1556e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.1535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.1514e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.1493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.1471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.1451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.1430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.1410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.1389e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.1368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.1347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.1325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.1303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.1281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.1260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.1239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.1218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.1198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.1178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.1157e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.1140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.1122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.1104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.1090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.1075e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.1061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.1046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.1032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.9307e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2850 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 138/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 2.9529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.8388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.8097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.7485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.6867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.6498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.6267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.6009e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.5779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.5604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.5565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.5495e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.5429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.5385e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.5355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.5376e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5381e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.5367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.5339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.5322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.5309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.5287e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.5267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.5252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.5241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.5225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.5207e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.5190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.5175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.5158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.5149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.5141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.5140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.5137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.5163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.5187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.5212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.5229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.5242e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.5255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.5265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.5271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.5305e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.5336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.5366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.5392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.5416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.5441e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.5469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.5493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.5513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.5533e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.5551e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.5566e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.5577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.5588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.5599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.5607e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.5615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.5622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.5629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.5634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.5638e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.5641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.5645e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.5647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.5649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.5649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.5650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.5649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5696e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5784e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.5825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.5862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.5898e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.5933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.5966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.5998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.6028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.6058e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.6086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.6112e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.6137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.6160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.6182e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.6202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.6221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.6241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.6259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.6276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.6293e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.6310e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.6325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.6340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.6354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.6367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.6379e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.6390e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.6401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.6411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.6420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.6430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.6438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.6447e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.6455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.6462e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.6469e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.6475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.6480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.6485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.6489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.6493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.6496e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 2.6863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2875 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 139/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.2279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 2.3365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.3884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.3669e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.3392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.3127e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.2910e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.2684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.2447e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.2260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.2146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.2044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.1975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.1928e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.1902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.1862e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.1817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.1773e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 2.1731e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.1682e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.1627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 2.1582e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.1545e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.1513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.1494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 2.1482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.1471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.1460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 2.1445e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.1428e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.1415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 2.1398e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.1377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.1357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.1341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 2.1323e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.1306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.1292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 2.1280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.1275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.1269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 2.1264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.1259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.1251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.1242e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 2.1232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.1224e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.1216e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 2.1209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.1205e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 2.1201e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.1196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1183e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 2.1169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.1160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.1152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 2.1143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.1158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.1172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.1185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 2.1198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.1209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.1219e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 2.1228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.1237e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.1244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 2.1249e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1254e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.1273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.1277e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.1280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.1281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.1283e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.1284e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1284e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1283e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1283e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.1280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1277e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.1275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1272e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1263e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1256e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1237e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1233e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1224e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1214e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.1209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1205e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.1194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.1173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.1154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1148e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.1128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.0325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2924 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 140/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.9561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.0281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.0828e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.0869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.0671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.0452e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.0282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.0088e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.9887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.9733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.9626e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.9503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.9419e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.9349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.9307e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.9259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.9200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.9151e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.9105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.9055e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.8998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.8943e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.8901e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.8854e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.8812e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.8777e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.8746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.8712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.8675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.8648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.8623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.8683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.8733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.8776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.8814e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.8848e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.8880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.8910e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.8943e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.8971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.8995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.9016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9058e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.9068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9099e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.9152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.9228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.9305e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9331e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.9342e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9361e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.9381e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9389e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.9404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.9421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9434e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.9437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9441e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.9449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9453e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.9458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.9461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.9457e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9456e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9454e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.9452e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9447e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.9441e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.9429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.9418e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.9403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9398e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.9388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9377e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.9372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.9352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.9347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.9342e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.9336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.9331e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.9325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.9320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.9314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.8622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2955 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 141/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.7624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.7540e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 1.7680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.7534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.7308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.7174e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.7074e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6852e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.6628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.6585e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.6562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6525e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6473e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.6454e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.6429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.6397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.6364e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.6337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.6310e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.6286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.6273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.6269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.6259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.6245e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.6231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.6217e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.6202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.6184e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.6082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.6070e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.6057e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.6044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.6041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.6050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.6058e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.6073e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6071e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6069e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6060e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6058e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6039e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6038e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6037e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6033e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.6024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.6020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.6016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.6013e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.6009e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.6005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.6002e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5994e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.6027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.6063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.6098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.6131e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.6164e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.6195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.6226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.6256e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.6285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.6313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.6340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.6366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.6392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.6416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.6440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.6464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.6487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.9210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2946 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 142/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.8138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.8279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.8194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.7809e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.7476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.7258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.7155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.7059e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.6930e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.6855e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.6820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.6783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.6749e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.6743e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.6751e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.6740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.6721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.6699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.6674e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.6647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.6610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.6579e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.6573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.6561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.6555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.6555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.6556e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.6552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.6546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.6537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.6529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.6526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.6519e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.6513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.6508e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.6501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.6497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.6495e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.6493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.6497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.6498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.6500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.6501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.6501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.6498e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.6495e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.6493e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.6488e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.6484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.6481e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.6477e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.6472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.6465e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.6459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.6453e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6412e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.6387e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.6379e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.6370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.6362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.6353e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.6353e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.6351e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.6346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.6340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6332e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6321e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6312e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6301e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6298e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6301e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.6306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.6308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.6310e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.6311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.6312e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.6313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.6314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.6314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.6313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.6313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.6313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.6312e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.6311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.6310e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.6323e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.6336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.6348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.6359e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.6371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.6382e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.6392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.6402e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.6411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.6420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.6428e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.6436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.6444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.6451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.7318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2973 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 143/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.4859e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.4929e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.5090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.4947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.4746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.4535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.4526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.4801e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.4986e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.5125e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.5237e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.5353e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.5432e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.5490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.5528e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.5560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.5597e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5632e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.5643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5657e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5670e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.5675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.5675e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.5674e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.5669e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.5659e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.5648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.5640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.5629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.5618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.5608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.5598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.5587e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.5574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.5560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5532e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5407e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5379e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5216e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5205e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5183e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5085e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5074e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5052e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.5020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.5009e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.4999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.4989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.4979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.4969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.4959e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.4948e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.4938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.4927e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.4917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.4907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.4897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.4887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.4877e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.4867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.4857e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.4848e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.4838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.4829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.4821e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.4813e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.4805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.4798e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.4790e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.4783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.4776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.4768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.4761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.4753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.4750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.4746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.4743e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.4739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.4313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3010 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 144/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 302ms/step - accuracy: 1.0000 - loss: 1.2043e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.2090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.2672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.2758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.2702e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.2595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.2522e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.2480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.2397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.2358e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.2339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.2295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.2255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.2188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.2169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.2153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.2122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.2113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2106e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2095e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2083e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2096e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2125e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2132e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2139e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.2165e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.2170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.2175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.2180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.2184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.2186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.2187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.2190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.2192e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.2194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2197e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.2195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2192e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.2187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.2171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.2168e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.2164e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.2161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.2157e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.2152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.2147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.2143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.2138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.2133e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.2129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.2125e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.2121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.2116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.2112e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.2108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.2103e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.2098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.2094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.2090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.2085e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.2080e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.2076e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.2071e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.2067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.2062e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2057e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2052e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2042e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2037e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2021e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.2007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.2002e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1997e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1988e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1964e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1960e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1955e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1951e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1946e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1929e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.1402e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3042 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 145/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.0773e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.1259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1102e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0959e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0927e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.0883e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.0849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.0823e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.0802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.0773e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.0741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.0705e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.0701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.0696e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.0683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.0673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.0665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.0655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.0646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.0637e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.0637e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.0634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.0627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.0621e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.0616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.0608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.0600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.0593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.0585e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.0577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.0569e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.0560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0545e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.0541e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0537e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0533e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0528e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0512e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0506e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.0500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.0495e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.0489e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.0483e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.0476e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.0470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.0463e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.0559e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.0650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.0737e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.0818e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.0895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.0968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.1039e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.1104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.1167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.1227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.1284e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.1338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.1389e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.1437e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.1485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.1530e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.1573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.1614e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.1653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.1690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.1726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.1759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.1791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.1822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.1851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.1878e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.1904e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.1929e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.1953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.1975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.1997e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2037e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2056e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2074e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2092e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2123e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2152e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2165e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2241e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2272e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2279e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2298e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2308e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2332e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.2895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3067 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 146/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 9.9963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 9.8988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 9.9062e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 9.8418e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 9.8169e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 9.7895e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.7752e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 9.7461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 9.6940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 9.6581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 9.6252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 9.5978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 9.5807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 9.5656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.5636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.5628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.5555e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 9.5459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.5405e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.5346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.5248e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.5131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.5066e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.4975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 9.4935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 9.4901e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 9.4874e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 9.4844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 9.4819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 9.4854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 9.4887e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 9.6395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 9.7745e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 9.8978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.0011e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.0113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.0210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.0311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.0405e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.0490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.0574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.0652e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.0727e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0796e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.0860e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.0976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.1028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.1077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.1126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.1172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.1215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.1255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.1293e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.1329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.1363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.1393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.1423e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.1451e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.1478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.1504e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.1529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.1553e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.1575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.1595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.1615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.1633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.1650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.1666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.1680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.1694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.1708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.1720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.1734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.1746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.1758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.1770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.1780e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.1790e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.1800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.1808e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.1816e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.1824e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.1831e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.1838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.1845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.1851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.1857e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.1863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.1868e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.1874e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.1878e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.1882e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.1886e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.1890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.1894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.1897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.1900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.1904e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.1907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.1909e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.1912e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.1914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.1915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.1917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.1918e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.1920e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.1921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.1921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.1922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.1922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.1923e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.1923e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.1923e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.1923e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.1923e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.1922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.1921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.1921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.1920e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.1795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3092 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 147/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.1623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 1.0960e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.0684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.0372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.0154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 9.9931e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 9.8802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 9.7875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.6769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.5931e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.5400e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.4875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.4478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.4249e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 9.4119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.3986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.3797e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.3687e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 9.3589e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 9.3477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.3318e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.3160e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.3032e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.2946e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 9.2898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.2858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.2829e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.2777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 9.2704e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.2624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.2562e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.2507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2434e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2266e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2182e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 9.2158e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 9.2453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2847e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 9.2957e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.3069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.3177e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 9.3279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.3372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.3471e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 9.3559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.3639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.3710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.3773e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 9.3829e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.3871e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.3911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 9.3954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.3990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.4028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 9.4064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.4100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.4131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.4157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.4183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.4208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.4232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.4251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.4269e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.4292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.4309e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.4326e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.4343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.4362e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.4375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.4387e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.4394e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 9.4401e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.4405e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.4405e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.4404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.4404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.4400e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.4393e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.4387e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.4380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.4371e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.4360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.4348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.4335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.4322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.4305e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 9.4290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 9.4276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 9.4260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 9.4246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 9.4234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 9.4225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 9.4213e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 9.4202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 9.4193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 9.4183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 9.4249e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 9.4312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 9.4373e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 9.4432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 9.4487e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 9.4540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 9.4593e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 9.4648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 9.4701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 9.4751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.4798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.4845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.4888e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.4928e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.4966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.5003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.5038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 9.9227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3112 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 148/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 9.0972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 9.2707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 9.3228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 9.1987e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 9.0393e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 8.8971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 8.8035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 8.7161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 8.6251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 8.5619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 8.5204e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 8.4757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.4558e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.4407e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.4301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.4161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.4027e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.3880e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.3735e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.3575e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.3385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.3201e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.3069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.2934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.2827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.2755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.2726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.2687e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.2637e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.2570e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.2522e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.2459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.2377e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.2299e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.2232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.2172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.2119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.2076e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.2040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.1993e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.1947e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.1900e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.1863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.1817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.1761e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.1711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.1666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.1617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.1573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.1530e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.1491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.1447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 8.1401e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 8.1352e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 8.0800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 8.0760e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 8.0723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 8.0684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 8.0647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 8.0611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 8.0577e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 8.0321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 8.0291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 8.0262e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 8.0234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 8.0232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 8.0226e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 8.0220e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 8.0220e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 8.0266e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 8.0307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 8.0343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 8.0379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 8.0417e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 8.0453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 8.0487e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 8.0521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 8.0555e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 8.0587e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 8.0615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 8.0643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 8.0669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 8.0694e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 8.0715e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 8.0736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 8.0756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 8.0774e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 8.0792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 8.0809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 8.0827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 8.0843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 8.0856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 8.0870e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 8.0883e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 8.0894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 8.0901e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 8.0909e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 8.0915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 8.0920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 8.1493e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3148 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 149/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 7.5299e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 7.7410e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.7731e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.6561e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.5867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 7.5470e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 7.5352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 7.5299e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 7.4996e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.4755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.4706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.4572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4595e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.5625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 9.4685e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0818e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.1747e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.2093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.2383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.2631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.2839e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3062e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.3255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.3424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.3569e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.3690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.3794e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.3883e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.3957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.4017e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.4067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.4110e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.4144e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.4172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.4194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.4212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.4224e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.4231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.4315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.4390e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.4458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.4519e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.4573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.4622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.4666e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.4704e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.4740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.4773e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.4802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.4826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.4851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.4872e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.4891e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.4908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.4922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.4934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.4945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.4955e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.4963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.4971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.4977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.4982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.4986e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.4988e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.4989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.4989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.4988e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.4987e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.4985e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.4983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.4981e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.4977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.4973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.4968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.4962e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.4956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.4949e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.4941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.4933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.4926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.4918e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.4910e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.4902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.4893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.4885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.4875e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.4866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.4856e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.4846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.4835e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.4825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.4814e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.4802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.4791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.4780e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.4768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.4756e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.4744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.4732e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.4720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.4707e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.4694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.4682e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.4669e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.4656e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.4643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.4630e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.4616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.4603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.4589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.4576e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.4563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.4549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.4536e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.4523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.4510e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.4496e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.2921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3119 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 150/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 294ms/step - accuracy: 1.0000 - loss: 8.1973e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 8.7793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 8.9297e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 8.9855e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 8.9573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 8.9565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 8.9657e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 9.0200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 9.0342e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 9.0417e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 9.0759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 1.0000 - loss: 9.0881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 9.0961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 9.1016e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 9.1037e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 9.0984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 9.0891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 9.0782e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 9.0686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 9.0548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 9.0359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 9.0184e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 9.0052e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 8.9911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.9784e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.9716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.9675e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.9611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 8.9539e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 8.9491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 8.9444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.9420e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.9374e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.9363e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.9367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.9365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.9359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.9353e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.9345e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.9324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.9289e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 8.9259e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 8.9243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 8.9227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 8.9196e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 8.9165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 8.9135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 8.9095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.9054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.9014e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.8976e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.8932e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 8.8881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 8.8825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 8.8774e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 8.8717e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 8.8654e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.7765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.7706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.7650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.7599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 8.7547e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 8.7492e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 8.7438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 8.7389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 8.7339e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 8.7304e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 8.7268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 8.7231e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 8.7193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 8.7155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.7117e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.7080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.7041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.7001e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.6960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.6919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.6876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.6831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.6786e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.6743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.6698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.6654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.6611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.6569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.6529e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.6488e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.6447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.6407e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.6366e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.6323e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.6281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.6243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.6203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.6166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.6128e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.6092e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.6054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.6021e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.5988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.5955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.5923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.5889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.5855e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.5822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.5789e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 8.1851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3156 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 151/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 8.6067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 8.2125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.1058e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.0189e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 7.8823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 7.8189e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 7.7908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 7.7512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 7.6882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 7.6481e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 7.6153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 7.5769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 7.5427e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 7.5152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 7.4937e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 7.4711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 7.4460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 7.4255e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 7.4088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 7.3910e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 7.3700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 7.3503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 7.3330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 7.3153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 7.3020e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 7.2905e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 7.2801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 7.2701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 7.2592e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 7.2491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 7.2407e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.2310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.2200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.2095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.2000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.1904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.1809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.1721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.1646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.1564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.1480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 7.1395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 7.1313e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 7.1231e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 7.1155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 7.1083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 7.1016e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 7.0955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 7.0899e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 7.0846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 7.0802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 7.0755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 7.0706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 7.0653e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 7.0611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 7.0567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 7.0517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 7.0469e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 7.0425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 7.0385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 7.0349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 7.0312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 7.0284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 7.0251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 7.0216e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 7.0179e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 7.0141e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 7.0100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 7.0053e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 7.0008e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.9965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.9922e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.9881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.9842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.9807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.9773e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.9737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.9703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.9668e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.9630e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.9591e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.9569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.9549e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.9526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.9504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 6.9482e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.9460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.9436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.9412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.9386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.9361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.9335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.9307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.9279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.9254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.9227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.9202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.9178e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 6.9157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.9135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.9112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.9089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.9066e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.9042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.9016e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.8963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.8935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.8909e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.8882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.8856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.8830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.8802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.8774e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.8747e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.8723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.8697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.8673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.8649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.8625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 6.5737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3196 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 152/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 5.6800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.7753e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.8583e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 5.8004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 5.7368e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 5.6919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 5.6963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 5.7048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.6889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.6914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.7024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.7038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.7044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.7078e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.7180e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.7234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.7263e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.7278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.7330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.7348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.7335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.7326e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.7325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.7317e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.7313e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.7340e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.7371e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.7406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.7428e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.7450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.7480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.7492e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.7484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.7476e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.7475e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 5.7474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 5.7489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 5.7505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.7550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.7584e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.7610e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.7631e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 5.7652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 5.7689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 5.7722e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 5.7772e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.7820e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.7862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.7901e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.7938e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.7972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.7998e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8018e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8047e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8058e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.8064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.8067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.8072e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.8075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.8077e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.8080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.8084e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.8086e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.8084e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.8083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.8083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.8083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.8078e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.8073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.8074e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.8071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.8070e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.8069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.8069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.8066e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.8061e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.8055e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.8050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.8045e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.8038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.8035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.8031e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.8025e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.8017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.8011e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.8007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.8000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.7992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.7984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.7975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.7964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.7953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.7942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.7931e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.7920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.7909e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.7899e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.7889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.7879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.7869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.7859e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.7849e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.7839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.7827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.7815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.7804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.7792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.7781e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.7770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.7759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.7749e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.7738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 5.7728e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 5.7718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.7707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.7695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.7682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.7670e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.7659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 5.6333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3233 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 153/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 6.1871e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 6.0085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.9790e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.8885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 5.7887e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 5.7385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 5.7071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 5.6676e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.6156e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.5785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.5480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.5186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.4954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.4792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 5.4649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 5.4508e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 5.4350e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 5.4191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.4041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.3916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.3794e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.3676e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 5.3583e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 5.3485e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 5.3390e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.3308e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.3251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 5.3208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 5.3170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 5.3121e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.2293e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.2234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.2179e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.2123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.2069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.2017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.1970e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.0861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.0839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.0817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.0797e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.0775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.0754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.0732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.0713e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.0692e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.0671e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.0649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.0629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.0608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.0586e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.0563e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.0542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.0519e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.0496e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.0475e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.0456e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.0436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.0416e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.0395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.0375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.0355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.0334e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.0314e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.0294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.0274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.0254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.0235e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.0217e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.0199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.0181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.0163e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.0145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.0127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.0107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.0088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.0068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.0049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 4.7701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3273 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 154/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 4.6007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 4.6505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.7054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.6980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.7005e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.7520e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.8135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.8298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.8187e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.8187e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.8178e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.8101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.7992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.8630e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.9174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.9604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.9933e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.0198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.0431e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.0600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.0708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.0818e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.0910e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.0963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.1004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.1033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.1054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.1057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.1050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.1029e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.1017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.0988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.0946e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.0903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.0856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.0811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.0759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.0707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.0661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.0609e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.0556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.0503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.0449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.0390e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.0327e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.0265e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 5.0202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 5.0139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 5.0074e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 5.0035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.9997e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.9953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.9906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.9866e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.9824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.9780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.9735e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.9690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.9646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.9601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.9559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.9520e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.9482e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.9441e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.9398e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.9357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.9316e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.9274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.9230e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.9186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.9144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.9100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.9057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.9015e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.8974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.8934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.8894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.8855e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.8828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 4.8805e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 4.8781e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 4.8757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 4.8732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.8708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.8685e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.8663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.8648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.8633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.8617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.8604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.8590e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.8575e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.8570e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.8564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.8557e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.8549e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.8541e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.8535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.8529e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.8521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.8512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.8503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.8494e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.8484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.8472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.8461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.8453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.8444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.8436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.8428e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.8419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.8413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.8407e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.8401e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.8395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.8389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.8383e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.8376e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.8369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.8362e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 4.7454e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3300 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 155/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 36s 305ms/step - accuracy: 1.0000 - loss: 5.7081e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 5.3015e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 1.0000 - loss: 5.5521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 291ms/step - accuracy: 1.0000 - loss: 5.5460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 5.4513e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 5.3515e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 5.2778e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 1.0000 - loss: 5.1960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 1.0000 - loss: 5.1110e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 1.0000 - loss: 5.0432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 1.0000 - loss: 4.9851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 1.0000 - loss: 4.9287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 1.0000 - loss: 4.8780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 1.0000 - loss: 4.8338e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 1.0000 - loss: 4.7979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 1.0000 - loss: 4.7615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 4.7286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 4.6980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.2147e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.2126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.2106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.2087e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.2068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.2049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.2030e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.2012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.1993e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.1975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.1955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.1936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.1916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.1897e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.1877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.1858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.1839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.1819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.1799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.1988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.2174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.2353e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.2526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.2699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.2868e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.3032e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.3192e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.3349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.3507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.3660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.3809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.3956e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.4099e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.4241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.4378e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.4514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.4655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.4798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 6.1833e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3288 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 156/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 6.8053e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 7.8122e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.5273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 8.5357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 8.4743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 8.3526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 8.2537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 8.1577e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 8.0392e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.9395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.8718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.8175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.7643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.7266e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.6948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.6720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.6453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.6224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.5986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.5716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.5438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.5164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.4925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.4669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.4424e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.4199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.3977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.3734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.3501e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.3288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.3077e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.2856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.2631e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 7.2410e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 7.2202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.1998e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.1798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.1618e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.1444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.1270e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.1111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.0949e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 7.0793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 7.0630e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 7.0460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 7.0294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 7.0135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 6.9977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 6.9826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 6.9678e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 6.9533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 6.9387e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 6.9237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 6.9093e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 6.8948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 6.8802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 6.8654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.8505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.8360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.8214e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.8072e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 6.7933e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 6.7795e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 6.7656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 6.7517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 6.7379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 6.7246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 6.7117e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 6.6987e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 6.6860e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 6.6737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 6.6614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 6.6494e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 6.6375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 6.6263e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 6.6151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 6.6040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 6.5929e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 6.5820e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 6.5714e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 6.5607e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 6.5500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 6.5395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 6.5290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 6.5187e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 6.5085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 6.4988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 6.4890e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 6.4793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 6.4695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 6.4599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 6.4503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 6.4406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 6.4310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 6.4216e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 6.4121e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.4027e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.3934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.3842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.3749e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.3658e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.3566e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.3476e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.3387e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.3297e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.3209e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.3122e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.3038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.2956e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.2876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 6.2797e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 6.2719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 6.2642e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.2567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 6.2493e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 6.2419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.2345e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.2273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.2201e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.2130e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 5.3661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3314 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 157/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 5.6739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.3518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.2285e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.0867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 4.9581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.8544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.7598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.6835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.6101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.5532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.5168e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.4814e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.4509e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.4265e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.4090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.4911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.6111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.8776e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.1146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.3278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.5176e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.6853e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.8347e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.9714e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.0936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.2026e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.3024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.3936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.4754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.5504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.6280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.6989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.7631e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.8221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.8759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9691e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 7.0091e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 7.0456e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 7.0793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 7.1097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 7.1380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 7.1637e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 7.1873e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 7.2085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.2275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.2705e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.3104e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.3474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.3813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.4129e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.4426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.4699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.4959e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.7143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.9218e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 8.1192e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 8.3417e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 8.6255e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 8.8963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.1547e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.4011e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.9980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0571e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1467e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.2357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.3227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.4066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.4872e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5710e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.6554e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.7371e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.8173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.8974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.1125e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.3297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.6852e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.1269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.6117e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.0926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.5720e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 5.1020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.6646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.2474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.8673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 7.5221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 8.4725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 9.6303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.0978e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2593e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.4496e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.6594e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8840e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1361e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.4083e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.7059e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.0268e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.3761e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.7638e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.1850e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.6440e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.1389e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.6712e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.2308e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.7995e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 7.3950e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 8.0080e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 8.6326e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 9.2686e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 9.9144e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.0574e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1257e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1945e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9997 - loss: 9.3871e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 - val_accuracy: 0.9739 - val_loss: 0.2300 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4974 Epoch 158/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 302ms/step - accuracy: 0.9980 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9980 - loss: 0.0053 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9980 - loss: 0.0052 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9981 - loss: 0.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9982 - loss: 0.0049 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9982 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9982 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9983 - loss: 0.0047 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9983 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9984 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9985 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9985 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9985 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9985 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9986 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9987 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9988 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9988 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9988 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9988 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9988 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 - val_accuracy: 0.9765 - val_loss: 0.2720 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4985 Epoch 159/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9998 - loss: 5.9691e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9998 - loss: 5.3897e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9998 - loss: 4.9734e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9998 - loss: 4.5746e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9999 - loss: 4.2363e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9999 - loss: 3.9711e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9999 - loss: 3.7510e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9999 - loss: 3.5773e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9999 - loss: 3.4306e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9999 - loss: 3.3103e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9999 - loss: 3.2073e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9999 - loss: 3.1283e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 3.0643e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 3.0044e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 2.9451e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 2.8864e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9999 - loss: 2.8300e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9999 - loss: 2.7753e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9999 - loss: 2.7228e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9999 - loss: 2.6720e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9999 - loss: 2.6249e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9999 - loss: 2.5802e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9999 - loss: 2.5378e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9999 - loss: 2.4992e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9999 - loss: 2.4621e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9999 - loss: 2.4264e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9999 - loss: 2.3916e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9999 - loss: 2.3577e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9999 - loss: 2.3247e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9999 - loss: 2.2926e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9999 - loss: 2.2614e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9999 - loss: 2.2310e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9999 - loss: 2.2014e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9999 - loss: 2.1727e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9999 - loss: 2.1448e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9999 - loss: 2.1177e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9999 - loss: 2.0917e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9999 - loss: 2.0663e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9999 - loss: 2.0416e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9999 - loss: 2.0175e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9999 - loss: 1.9941e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9999 - loss: 1.9713e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9999 - loss: 1.9491e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9999 - loss: 1.9274e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9999 - loss: 1.9063e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9999 - loss: 1.8857e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9999 - loss: 1.8657e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9999 - loss: 1.8462e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9999 - loss: 1.8273e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.8088e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.7908e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.7732e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.7560e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.7391e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.7226e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.7065e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.6907e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.6752e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.6601e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.6453e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.6309e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.6168e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.6029e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5893e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5760e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5629e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5501e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5375e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5252e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5131e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5013e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.4897e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.4783e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.4671e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.4561e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.4453e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.4347e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.4242e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.4140e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.4039e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3939e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3842e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.3746e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.3651e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.3558e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.3467e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.3377e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.3288e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.3201e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.3115e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.3031e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2947e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.2865e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2784e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2705e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.2626e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2549e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2472e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.2397e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.2323e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.2250e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.2178e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.2107e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.2036e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1967e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1899e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1832e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1765e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1699e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1635e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1571e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1508e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1446e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1384e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1323e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1264e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1204e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1146e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1088e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1031e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 4.2418e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.2802 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4987 Epoch 160/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 6.0933e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 5.9288e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 5.8468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 5.6902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 5.5880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 5.6723e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 5.7085e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 5.7117e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 5.6822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 5.6641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.6542e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 5.6345e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.6186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.6031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.5867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.5661e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.5433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.5200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.5573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.5837e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.6147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.6414e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.6633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.6792e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.6927e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.7056e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.7161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.7232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 5.7286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 5.7343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 5.7387e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 5.7409e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 5.7405e-06 - mean_absolute_error: 0.5000 - 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0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.4159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.4093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 5.4027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.3960e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.3893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 5.3825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.3758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.3694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.3629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 5.3564e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.3499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.3436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 5.3372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.3309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.3246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.3193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 5.3139e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 5.3085e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 5.3031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 5.2977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 5.2922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 5.2867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 5.2812e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 5.2757e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 4.6197e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2866 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 161/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.2172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 1.0000 - loss: 3.2882e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 3.3296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 3.2795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 3.2265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.1793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.1505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 3.1212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 3.0929e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 3.0698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 3.0552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 3.0403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 3.0304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 3.0234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 3.0229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 3.0193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 3.0158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 3.0120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 3.0089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 3.0119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 3.0122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 1.0000 - loss: 3.0130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 1.0000 - loss: 3.0147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 1.0000 - loss: 3.0150e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.0158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.0165e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.0170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.0167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 3.0158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 3.0145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 3.0134e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 3.0116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 3.0095e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 3.0077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.0063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.0045e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.0034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.0023e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 3.0014e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.9998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.9980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.9961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.9941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.9924e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.9907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.9890e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.9874e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.9854e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.9838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.9822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.9808e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.9791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.9774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.9756e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.9739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.9721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.9700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.9680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.9661e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.9643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.9626e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.9608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.9591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.9598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.9605e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.9609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.9613e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.9615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.9615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.9615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.9615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.9614e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.9612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.9610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.9609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.9606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.9602e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.9597e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.9644e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.9688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.9728e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.9768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.9807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.9843e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.9878e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.9911e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.9944e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.9975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.0003e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.0030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.0055e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.0079e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.0100e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.0121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.0140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.0158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.0175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.0192e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.0208e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.0223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.0236e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.0249e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.0260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.0271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.0280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.0289e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.0297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.0305e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.0312e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.0319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.0325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.0330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.0334e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.0338e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.0341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.0344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.0345e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.0346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.0347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.0347e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 3.0330e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2947 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 162/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.8327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 2.8436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.8611e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.8105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.7628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.7214e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.6911e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.6557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.6191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.6021e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.5884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.5725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.5594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.5482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.5401e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.4985e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.4886e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.4782e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - 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2.4374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.4335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.4294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.4257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.4215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.4186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.4162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.4134e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.3771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.3779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.3785e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.3791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.3795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.3800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.3803e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.3805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.3807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.3808e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.3810e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.3810e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.3811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.3811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.3811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.3810e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.3809e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.3807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.3805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.3803e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.3800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.3797e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.3794e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.3790e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.3787e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.3783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.3779e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.3774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.3770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.3765e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.3761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.3755e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.3750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.3744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.3738e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 2.3034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2996 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 163/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.7969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 1.8383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.8813e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.8637e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.8505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.8333e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.8247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.8177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.8043e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.7973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 1.7937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 1.0000 - loss: 1.7883e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 1.7837e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 1.7819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 1.7818e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.7804e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.7785e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.7764e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.7754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.7738e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.7709e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.7683e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.7668e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.7654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.7642e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7637e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.7624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.7588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.7573e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.7554e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.7535e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.7518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.7501e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.7485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.7471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.7459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.7444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.7430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.7417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.7406e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.7393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.7379e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.7365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.7352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.7337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7323e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7301e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7289e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.7277e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.7264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.7252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7239e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.7185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.7173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.7161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.7149e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.7137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.7124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.7112e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.7101e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.7090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.7078e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.7067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.7057e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.7046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.7036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.7026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.7017e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.7007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6997e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6988e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.6978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.6947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.6905e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6896e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6886e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.6876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.6849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.6839e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.6830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.6820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.6810e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.6800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.6791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.6781e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.6772e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.6762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.6754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.6746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.6737e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.6728e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.6719e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.6711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.6702e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.6694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.6686e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.6678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.6670e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.6662e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.6655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.6647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.6640e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.6632e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.6624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.6617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.6609e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 1.5695e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3059 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 164/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 1.4526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 1.4326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.4360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.4208e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.4162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.4163e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.4260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.4276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.4226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.4179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 1.4158e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 1.4126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.4108e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.4103e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.4103e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.4087e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.4072e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.4053e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.4041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.4026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.4002e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.3976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.3953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.3931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.3912e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.3897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.3885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.3870e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.3855e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.3841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.3829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.3817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.3802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.3788e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.3777e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.3763e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.3752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.3743e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.3734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.3722e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.3710e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.3699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.3688e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.3676e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.3663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.3649e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.3641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.3632e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.3625e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.3621e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.3620e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.3617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.3613e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.3608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.3603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.3599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.3594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.3577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.3572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.3567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.3563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.3557e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.3551e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.3545e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.3539e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.3533e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.3525e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.3518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.3511e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.3503e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.3497e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.3490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.3484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.3478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.3471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.3464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.3460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.3455e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.3449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.3444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3431e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3427e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3423e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3419e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3413e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3408e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.3405e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.3402e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.3400e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.3397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.3394e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.3391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.3388e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.3387e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.3386e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.3385e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.3383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.3382e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.3380e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.3378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.3376e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.3374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.3372e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.3370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.3368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.3365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.3362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.3360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.3357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.3354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.2996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3109 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 165/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.2298e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.2029e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.2183e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.2061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1778e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1551e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1508e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1453e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.1370e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.1346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1333e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.1316e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.1297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1280e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1264e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1216e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1205e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.1196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.1200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.1202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.1206e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.1207e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1208e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.1213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.1213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 1.1212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.1213e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 1.1216e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.1217e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.1222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.1227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.1232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.1235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.1282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.1326e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.1366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.1439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1473e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1505e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.1534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1585e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.1629e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.1682e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1740e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1753e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1764e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1791e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1798e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1860e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1878e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1932e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1942e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1951e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1956e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1959e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1962e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1965e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1970e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.1979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.1980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 299ms/step - accuracy: 1.0000 - loss: 1.1980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 1.1981e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 1.1981e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 299ms/step - accuracy: 1.0000 - loss: 1.1980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 1.1980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 1.1980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 299ms/step - accuracy: 1.0000 - loss: 1.1980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.1979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.1979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.1978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 299ms/step - accuracy: 1.0000 - loss: 1.1977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.1976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.1975e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 299ms/step - accuracy: 1.0000 - loss: 1.1974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.1973e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.1971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.1970e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 299ms/step - accuracy: 1.0000 - loss: 1.1968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 1.1763e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3141 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 166/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.1647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.1283e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.1289e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.1094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.0902e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.0635e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0403e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.0317e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.0246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.0179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.0173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.0179e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.0186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.0206e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.0217e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.0222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.0226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.0225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.0221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 1.0218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.0215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.0210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.0208e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 1.0209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.0208e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.0204e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 1.0199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.0198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.0198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 1.0200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.0198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.0197e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 1.0195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.0193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0189e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.0188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.0188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.0188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.0188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.0188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.0188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.0187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.0185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.0184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.0181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.0178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.0175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.0173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.0170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.0168e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.0166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.0164e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.0162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.0159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.0155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.0151e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.0147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.0143e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.0139e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.0135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.0130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.0125e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.0120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.0115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.0110e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.0104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0099e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0093e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.0088e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.0084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.0082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.0080e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.0077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.0073e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.0070e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.0066e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.0063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0059e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0055e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0040e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0037e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0025e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0011e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0003e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.9993e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.9955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.9916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.9875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.9835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.9795e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.9753e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.9710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.9666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.9624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.9579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.9536e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.9493e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.9453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.9411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.9369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.9327e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.9285e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.9242e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.9197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.9152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.9107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.9062e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 9.3644e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3179 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 167/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 8.5718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.9843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 9.1186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 9.0522e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.9308e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 8.8414e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 8.7645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 8.6947e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.6108e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 8.5622e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 8.5334e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 8.4966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.4734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.4690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.4702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.4648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.4540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.4423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.4325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.4197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.4064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.3945e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.3849e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.3766e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.3733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.3721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.3736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 8.3730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 8.3780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 8.3811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 8.3825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.3871e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.3898e-07 - 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0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.3973e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.3949e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.3927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.3903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.3877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.3852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.3827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.3801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.3772e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.3743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.3714e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.3684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.3655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.3627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.3600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.3578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.3556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.3532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.3509e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.3486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.3463e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.3440e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.3417e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.3392e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 8.0441e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3215 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 168/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 7.6137e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 7.6247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 9.2115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.2037e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.3647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3818e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3689e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3405e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2937e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2797e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2519e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2390e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2268e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.1917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.1999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2114e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2205e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.2218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2224e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.2223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.2304e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.2313e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 1.2318e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 1.2321e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.2320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.2314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 1.2306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.2297e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.2285e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.2270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 1.2254e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.2238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.2220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 1.2210e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2199e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 1.2162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.2148e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.2132e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 1.2116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 1.2099e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 1.2082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 1.2064e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 1.2046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 1.2028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.2011e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.1995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1979e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1962e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.1945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1928e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1911e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.1893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1858e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.1841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1823e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1789e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.1772e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1737e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.1719e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1703e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1687e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.1655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1639e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.1608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1577e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.1562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1531e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1516e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.1500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1486e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.1458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1443e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1434e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.1425e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1405e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.1385e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1364e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.1353e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1343e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1333e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.1322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1312e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1302e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.1281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1261e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.1250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1219e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.1209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 9.9710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3198 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 169/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 8.8009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 8.8894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.8548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 8.6619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.5365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.4763e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.4439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 8.3754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 8.2908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 8.2205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 8.1702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 8.1265e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 8.0938e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 8.0684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 8.0515e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 8.0331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.0205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.0545e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.0904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.1166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.1322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - 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8.1935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 8.1967e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 8.1985e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 8.1975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 8.1944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 8.1906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 8.1876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 8.1833e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.4898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.5046e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.5185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 8.5318e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.5443e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.5566e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.5682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.5795e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.5904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.6011e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.6113e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.6212e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.6307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.6403e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.6496e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.6583e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.6671e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.6756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.6836e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.6912e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.6986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.7058e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.7125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.7195e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.7263e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.7327e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.7387e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.7446e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.7502e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.7556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.7607e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.7654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.7699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.7743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.7785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 9.2772e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3234 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 170/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 7.6815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 7.7137e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 7.7999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 7.6649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 7.5274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 7.4740e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 7.4524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 7.4132e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 7.3617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 7.3198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 7.3094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 7.2946e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 7.2863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 7.2968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 7.3078e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 7.3131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 7.3220e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 7.3325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.3403e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.3430e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.3421e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.3433e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 7.3455e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 7.3449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 7.3439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 7.3513e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 7.3588e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 7.3723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.3825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.3917e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.4020e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 7.4094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 7.4141e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 7.4174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 7.4209e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 7.4228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 7.4250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.4271e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.4288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.4291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.4282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.4294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.4326e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.4348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.4354e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.4357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.4364e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.4364e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.4365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.4370e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.4377e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.4379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.4380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.4376e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.4392e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.4423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.4442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.4466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.4491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 7.4590e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 7.4682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 7.4773e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.4861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.4941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 7.5015e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.5084e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.5148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.5204e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 7.5250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.5301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.5349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 7.5390e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.5429e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.5465e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.5499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 7.5538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.5571e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.5600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.5629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.5653e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.5671e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.5689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.5707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.5721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.5736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.5750e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.5761e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.5769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.5775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.5779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.5781e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.5780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.5776e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.5770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.5765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.5757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.5747e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.5737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.5726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.5713e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.5699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.5682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.5667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.5916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.6156e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.6388e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.6613e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.6831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.7041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.7245e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.7443e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.7633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.7817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.7998e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.8173e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.8342e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.8505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.8663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.8817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.8966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 9.6716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3208 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 171/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 9.6921e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 9.1120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.8578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.6144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.3844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.1914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 8.0483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 7.9343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 7.8108e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 7.7162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 7.6422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 7.5686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.5010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4005e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 7.3619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 7.3258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 7.2914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.2636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.2446e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.2211e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 7.2010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 7.1828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 7.1639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 7.1469e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.1331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.1225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.1127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.1073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.1006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.0941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 7.0863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 7.0806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.0758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.0718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.0669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.0633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.0600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.0575e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.0539e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.0509e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.0480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.0454e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.0422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.0381e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.0344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.0309e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 7.0275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.0243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.0215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.0185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 7.0150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.0115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.0087e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 7.0057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 7.0022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.9985e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.9946e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.9908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.9867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.9835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.9802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.9770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.9734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.9695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.9655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.9617e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 6.9451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 6.9478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 6.9502e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 6.9768e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 7.0025e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.0274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.0510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.0735e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.0954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.1161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.1360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.1552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.1737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.1915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.2085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.2251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.2411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.2566e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.2713e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.2854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.2992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.3123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.3249e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.3372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.3490e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.3603e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.3711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.3815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.3916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.4012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.4102e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.4190e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.4274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.4356e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.4436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.4514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.4589e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.4663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 7.4734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.4802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.4866e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 7.4930e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.4989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.5046e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.5101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 7.5152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 8.1243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3240 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 172/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.3833e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 6.1885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.4193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.5532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 6.5741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 6.5970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 6.6156e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 6.6119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.5867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.5720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.5629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.5584e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.5658e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.5756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.5806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.5754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.5715e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.5702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.5755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.5761e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.5710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 6.5643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.5589e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.5503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.5414e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.5341e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.5286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.5208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.5123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.5031e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.4941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.4842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 6.4733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 6.4627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 6.4527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 6.4418e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 6.4333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 6.4258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.4185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 6.4106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.4025e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.3940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 6.3857e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 6.3776e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 6.3687e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.3604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.3524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.3440e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.3361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.3286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.3214e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.3140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.3063e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.2987e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.2923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.2856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.2790e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.2725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 6.2661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.2603e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.2543e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 6.2514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.2485e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.2453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 6.2419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.2386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.2353e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.2321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 6.2290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 6.2261e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 6.2232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 6.2222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 6.2214e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 6.2204e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 6.2197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 6.2187e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 6.2175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 6.2161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 6.2146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 6.2129e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 6.2109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 6.2089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 6.2067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 6.2043e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 6.2017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 6.1994e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.1971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.1947e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.1923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.1908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.1893e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.1876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.1858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.1839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.1834e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.1826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.1818e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.1811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.1803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.1793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.1782e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.1771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.1760e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.1747e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.1734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.1719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.1705e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.1690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.1674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.1659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.1643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.1626e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.1608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.1592e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.1576e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.1559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.1541e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.1523e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.1507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.1490e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 5.9499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3287 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 173/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 5.1298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 5.2596e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 5.2948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 5.2503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 5.3088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 5.3208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 5.3185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 5.3107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 5.2877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 5.2680e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 1.0000 - loss: 5.2478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 5.2238e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 5.2013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 5.1940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 5.2203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 5.2418e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 5.2554e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.2644e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.2765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.2841e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.2862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.2879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.2889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.2866e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.2839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.2810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.2785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.2745e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.2738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.2720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.2698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.2666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.2616e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.2647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.2674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.2689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.2699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.2706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.2733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 5.2748e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 5.2752e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 5.2747e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.2741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.2728e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.2711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.2706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.2706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.2698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.2691e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.2685e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.2677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.2660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.2639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.2627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.2612e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.2593e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.2568e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.2544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.2520e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.2493e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.2467e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.2445e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.2426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.2404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.2383e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.2360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.2337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.2313e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.2286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.2259e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.2232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.2204e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.2189e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.2174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.2161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.2148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.2133e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.2117e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.2100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.2086e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.2080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.2071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.2063e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.2056e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.2050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.2045e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.2041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.2035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.2033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.2029e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.2024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.2018e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.2010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.2001e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.1991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.1981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.1971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.1961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 5.1951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.1940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.1927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.1919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.1910e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.1900e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.1889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.1877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.1864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.1852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.1839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.1826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.1813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.1799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.1785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1902e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.2038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.2103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 5.9811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3315 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 174/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 4.7540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 4.8867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.0570e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.0256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.0313e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.0208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.0074e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.9910e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.9666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.9533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 4.9520e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 4.9460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.9439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.9475e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.9524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 4.9544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.9550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.9521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.9506e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.9517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.9510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.9514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.9555e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.9577e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.9631e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.9700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.9772e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.9826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 4.9882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 4.9979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 5.0065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 5.0150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 5.0221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 5.0290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 5.0363e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.0421e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.0479e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 5.0543e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 5.0604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.0654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.0703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.0748e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 5.0798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 5.0843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 5.0878e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 5.0911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 5.0944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 5.0974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 5.1017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 5.1061e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 5.1107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 5.1146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 5.1185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 5.1222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 5.1258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.1291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.1318e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.1346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.1374e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.1399e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.1430e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.1461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.1492e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.1517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.1541e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.1562e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.1583e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.1600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.1612e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.1625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.1637e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.1646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.1654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.1663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.1675e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.1684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.1690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.1693e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.1696e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.1697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.1695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.1695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.1698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.1698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.1703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.1708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.1714e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.1721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.1726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.1730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.1734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.1737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.1738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.1739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.1740e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.1739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.1738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.1736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.1733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.1729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.1724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.1719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.1715e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.1710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.1704e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.1698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.1693e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.1687e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.1681e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.1679e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.1676e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.1673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.1669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 5.0738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3331 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 175/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.7499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 1.0000 - loss: 5.4598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 5.4041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 5.3114e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.2370e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 5.1628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 5.0944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 5.0329e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.9784e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.9272e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.8871e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.8480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.8246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.8052e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.7915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.7726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.7556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 4.7401e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.7253e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.7115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.6958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.6805e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.6681e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.6548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.6423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.6308e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.6237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 4.6162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.6093e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.6040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 4.5989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 4.5931e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.5879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.5832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.5802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.5761e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.5720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.5684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.5647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.5607e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.5571e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.5544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.5519e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.5491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.5459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.5428e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.5404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.5376e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.5349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.5324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.5302e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.5277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 4.5251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 4.5225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 4.5199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.5175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.5148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.5121e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.5095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 4.5065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 4.5050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 4.5035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 4.5030e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 4.5022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 4.5012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 4.5002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 4.4990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 4.4976e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 4.4965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 4.4953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 4.4942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 4.4929e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 4.4917e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 4.4906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 4.4894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 4.4882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.4869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.4859e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 4.4849e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.4839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.4826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 4.4813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.4800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.4786e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.4771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 4.4759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.4747e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.4735e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 4.4721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.4707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.4694e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 4.4681e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.4666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.4651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.4638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 4.4624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.4611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.4599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 4.4586e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.4573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.4560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.4546e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 4.4531e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 4.4516e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 4.4500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.4484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.4468e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.4451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.4434e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.4417e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.4400e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.4383e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.4365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.4346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.4328e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.4310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.4292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.4274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.4256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.4237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 4.2067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3363 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 176/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 5.0288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 4.7256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 4.5045e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 4.2985e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 4.1641e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.0683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 4.0172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.9804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.9518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.9273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.9053e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.8857e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.8700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.8567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.8452e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.8321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.8183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.8078e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.7992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.7935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.7863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - 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3.7580e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.7544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.7512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.7482e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.7439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.7502e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.7570e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.7621e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.8839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.8853e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.8866e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.8877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.8887e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.8897e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.8906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.8913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.8919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.8926e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.8930e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.8935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.8940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.8945e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.8949e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.8951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.8954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.8955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.8956e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.8955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.8954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.8953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.8950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.8949e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.8948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.8946e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.8944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.8941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.8938e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.8935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.8932e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.8928e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.8923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.8918e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.8912e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 3.8254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3398 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 177/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.0793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 3.1712e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.2171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.1869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.1596e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.1396e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.1275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.1214e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.2321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.3151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.3711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.4052e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 3.4335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.4592e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.4798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.4974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.5448e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.5523e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.5582e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.5645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.5682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.5723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.5763e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.5801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.5827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.5849e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.5863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.5871e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.5870e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.5857e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.5849e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.5845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.5834e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.5820e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.5808e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.5794e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.5788e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.5779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.5775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.5767e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.5757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.5742e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 3.5724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 3.5710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 3.5692e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 3.5672e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 3.5654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 3.5636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 3.5615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 3.5592e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 3.5567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 3.5545e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 3.5534e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 3.5518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 3.5501e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 3.5487e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 3.5472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 3.5464e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 3.5462e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.5460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.5456e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.5449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.5440e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.5431e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.5423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.5412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.5401e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.5390e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 3.5378e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.5367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.5355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.5343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.5330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.5317e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.5302e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.5288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.5272e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.5255e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.5237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.5220e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.5205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.5190e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.5176e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.5162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.5146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.5131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.5116e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.5100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.5086e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.5071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.5056e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.5042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.5028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.5014e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.4999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.4986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.4973e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.4960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.4947e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.4934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.4921e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.4907e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.4894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.4882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.4869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.4857e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.4845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.4833e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.4822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.4810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.4798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.4787e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.4775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.4762e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.4749e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.4737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.4724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 3.3172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3431 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 178/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 294ms/step - accuracy: 1.0000 - loss: 2.9466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 3.1333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.4291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 3.6273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.7394e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 3.7723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 3.7781e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 3.7606e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.7266e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 3.6963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 3.6673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.6368e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.6070e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.5860e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 3.5677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 3.5552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 3.5417e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 3.5279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.5143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.5022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.4885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.4758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.4640e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.4523e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.4418e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.4329e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.4261e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.4198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 3.4131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 3.4073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 3.4022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 3.3969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 3.3923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 3.3881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 3.3842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 1.0000 - loss: 3.3801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 1.0000 - loss: 3.3765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 3.3727e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 1.0000 - loss: 3.3689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 1.0000 - loss: 3.3653e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 1.0000 - loss: 3.3611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 3.3567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 3.3525e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 3.3491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 3.3452e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 3.3412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 3.3373e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 3.3333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 3.3294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 3.3259e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 3.3225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 3.3191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.3162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.3140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.3118e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.3096e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.3072e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.3050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.3027e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.3004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.2981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.2957e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.2936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.2914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.2890e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2844e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 3.2645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2623e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2558e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2488e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.2419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.2397e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.2376e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.2355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.2333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.2312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.2291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.2269e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.2247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.2225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.2222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.2218e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.2213e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.2209e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.2205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.2200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.2193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.2189e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.2184e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.2179e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.2173e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.2167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.2161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.2154e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.2146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.2138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.2131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.2123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.2115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.2106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.2097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.2088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.2080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.2072e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.2063e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.2054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 3.0981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3461 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 179/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.2891e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 1.0559e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 9.2507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 8.3102e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 7.6541e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 1.0000 - loss: 7.1436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 6.7529e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 6.4408e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 6.1699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.9436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.7485e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.5736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 5.4296e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 5.3022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 5.1888e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 5.0834e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.9869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.9027e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 4.8250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.7604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.6994e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 1.0000 - loss: 4.6455e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.5942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.5444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.4975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 1.0000 - loss: 4.4536e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 4.4119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 4.3714e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 1.0000 - loss: 4.3328e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 4.2961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 4.2613e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 4.2287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 1.0000 - loss: 4.1968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 4.1664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 4.1375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 1.0000 - loss: 4.1092e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 4.0820e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 4.0573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 1.0000 - loss: 4.0351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 4.0136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.9922e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.9718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 1.0000 - loss: 3.9520e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.9331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.9143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 1.0000 - loss: 3.8961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.8786e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.8614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 1.0000 - loss: 3.8447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.8287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.8133e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.7984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 1.0000 - loss: 3.7836e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.7691e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.7550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 1.0000 - loss: 3.7412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.7275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.7143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 1.0000 - loss: 3.7017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.6891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.6769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.6651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 1.0000 - loss: 3.6537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.6424e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.6313e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 299ms/step - accuracy: 1.0000 - loss: 3.6204e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 3.6097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 299ms/step - accuracy: 1.0000 - loss: 3.5992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 3.5888e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.5785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.5686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.5588e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 3.5494e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.5402e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.5312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 3.5224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.5136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.5051e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 3.4968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.4887e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.4807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.4728e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.4651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.4576e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.4503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.4432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.4364e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.4298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.4232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.4168e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.4105e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.4043e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.3981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.3920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.3860e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.3800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.3742e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.3685e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.3632e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.3579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.3526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.3474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.3422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.3370e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.3319e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.3268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.3218e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.3167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.3118e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.3078e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.3039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.3000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.2961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.2923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.2885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.2847e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.2808e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.2770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.2733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.2696e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.8261e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3482 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 180/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.7512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 2.8862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.9215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.8769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.8289e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.7974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.7989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.7911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.7749e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.7583e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.7480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.7358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.7246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.7164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.7081e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.6992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.6914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.6848e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.6793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.6724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.6638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.6553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.6488e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.6423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.6368e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.6395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.6544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.6669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.6769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.6858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.6937e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.7007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7062e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.7148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7219e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.7262e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.7301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.7333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.7360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.7384e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.7407e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.7424e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.7434e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.7442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.7449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.7450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.7450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.7454e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.7453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.7451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.7448e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.7444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.7437e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.7430e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.7422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.7413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.7404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.7395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.7362e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.7356e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.7348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.7339e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.7330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.7320e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.7309e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.7297e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.7286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.7276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.7264e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.7252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.7239e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.7226e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.7212e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.7198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.7184e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.7170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.7155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.7140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.7125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.7110e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.7095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.7080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.7064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.7049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.7034e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.7018e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.7002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.6987e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.6972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.6959e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.6946e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.6933e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.6920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.6907e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.6894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.6881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.6868e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.6855e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.6843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.6830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.6817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.6805e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.6792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.6780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.6767e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.6754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.6743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.6731e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.6719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.6706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.6694e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.6682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.6670e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 2.5192e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3502 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 181/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.3880e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.3569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.4653e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.4919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.4924e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.4813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.4783e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.4751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.4592e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.4416e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.4269e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.4132e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.4041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.3990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.3947e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.3886e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.3818e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.3754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.3748e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.3732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 2.3693e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.3652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.3614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.3642e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.3686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.3720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.3749e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.5814e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.7662e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.9319e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 3.0817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.2167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.3382e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.4766e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.6028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.7626e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 3.9089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 4.0508e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.1817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.3169e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 8.4666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 9.5228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.0523e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.1462e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.2551e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.3575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.4541e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.5453e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.7144e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.8218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.9314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.1214e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.3020e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.4743e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.6384e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.8341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.0246e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.2195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.4181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.6260e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 3.8267e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 4.1186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 4.4825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 4.9416e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.4062e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.9550e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 6.5393e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.1481e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.8389e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 8.6673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.6128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0675e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.1819e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.3104e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.4686e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.6480e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.8486e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.0780e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.3282e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.5922e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.8835e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.1937e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.5293e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.8912e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.2682e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.6767e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.1193e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.5820e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.0844e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.6148e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.1618e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.7167e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.2946e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.8860e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.4892e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0114e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0756e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.1421e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2114e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2828e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.3567e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.4346e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5148e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5953e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9999 - loss: 1.6772e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9999 - loss: 1.7619e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9999 - loss: 1.8478e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9999 - loss: 1.9342e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9999 - loss: 2.0213e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9999 - loss: 2.1100e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9999 - loss: 2.2004e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9999 - loss: 2.2906e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9996 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 - val_accuracy: 0.9751 - val_loss: 0.3388 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4984 Epoch 182/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9984 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9983 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9983 - loss: 0.0048 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9984 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9984 - loss: 0.0045 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9985 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9985 - loss: 0.0043 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9986 - loss: 0.0041 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9987 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  13/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9987 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9989 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9990 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9993 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9994 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 - val_accuracy: 0.9757 - val_loss: 0.2848 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4984 Epoch 183/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9995 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9995 - loss: 0.0013 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - 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━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9996 - loss: 0.0012 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - 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━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9996 - loss: 0.0011 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - 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━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9996 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9996 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9996 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9996 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9997 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9997 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9997 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9997 - loss: 0.0010 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9997 - loss: 9.9914e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9997 - loss: 9.9559e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9997 - loss: 9.9204e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9997 - loss: 9.8851e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9997 - loss: 9.8498e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9997 - loss: 9.8147e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9997 - loss: 9.7797e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9997 - loss: 9.7448e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9997 - loss: 9.7102e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9997 - loss: 9.6757e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9997 - loss: 9.6413e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9997 - loss: 9.6071e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9997 - loss: 9.5731e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9997 - loss: 9.5392e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9997 - loss: 9.5054e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9997 - loss: 9.4719e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9997 - loss: 9.4385e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9997 - loss: 9.4052e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9997 - loss: 9.3721e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9997 - loss: 9.3393e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9997 - loss: 9.3066e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9998 - loss: 5.4141e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4998 - val_accuracy: 0.9768 - val_loss: 0.2832 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4986 Epoch 184/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 1.1484e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.1027e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0797e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.0352e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0007e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 9.7438e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 9.5391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 9.3512e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 9.1802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 9.1010e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 9.0392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.9707e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.9171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.8685e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.8235e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.7708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.7150e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.6594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.6122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.5633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.5111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.4606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.4135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.3660e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.3209e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.2884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.2560e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.2212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 8.1855e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 8.1490e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 8.1129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.0760e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.0381e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.0007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 7.9650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 7.9295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 7.8954e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 7.8620e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 7.8293e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 7.8253e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 7.8194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 7.8121e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 7.8034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 7.7934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 7.7820e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 7.7701e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 7.7591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 7.7474e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 7.7355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 7.7234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 1.0000 - loss: 7.7109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 7.6977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 7.6838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 7.6692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 1.0000 - loss: 7.6543e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 7.6392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 7.6236e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 1.0000 - loss: 7.6077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 7.5921e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 7.5762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 7.5604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 1.0000 - loss: 7.5446e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 7.5289e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 7.5129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 7.4967e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 7.4803e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 7.4639e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 7.4472e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 7.4303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 7.4135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 7.3968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 7.3800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 7.3636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 7.3475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 7.3315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 7.3153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 7.2990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 7.2827e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 7.2665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 7.2502e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 7.2339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 7.2177e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 7.2016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 7.1856e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 7.1698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 7.1541e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 7.1385e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 7.1228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 7.1071e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 7.0915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 7.0759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 7.0604e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 7.0449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 7.0296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 7.0145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.9995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.9845e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.9700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.9555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.9410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.9269e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.9127e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.8987e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.8846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.8707e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.8569e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.8433e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.8296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.8165e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.8035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.7906e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.7777e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.7648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.7520e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.7392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 6.7265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.7137e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.7010e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.6884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.6758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 5.1809e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.2943 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 185/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.3484e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.3843e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.3733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.2926e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.2360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.1929e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.1572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.2851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.3634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.4130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.4487e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.4682e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.4830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.4920e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.4993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.5005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 3.4991e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  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━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 3.4399e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.4327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.4265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 3.4193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.4112e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.4027e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.3941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.3853e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.3758e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.3664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.3582e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.3499e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.3430e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.3362e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.3302e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.3237e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.3169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.3099e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.3032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.2961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.2886e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.2814e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.2745e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.2674e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.2610e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.2546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.2485e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.2421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.2356e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.2291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.2227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.2161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.2097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.2034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.1974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.1914e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.1857e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.1801e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.1746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.1690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.1635e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.1580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.1526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.1471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.1415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.1360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.1306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.1251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.1198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.1146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.1097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.1047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.0997e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.0947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.0898e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.0849e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.0800e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.0750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.0702e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.0654e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.0607e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.0561e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.0516e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.0471e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.0426e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.0381e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.0337e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.0292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.0247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.0203e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.0160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.0118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.0076e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.0035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.9995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.9955e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.9915e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.9874e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.9834e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.9793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.9752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.9712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.9672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.9633e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.9594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.9556e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.9518e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.9480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.9442e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.9404e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.9366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.9329e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.9291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.9253e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.9217e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.9180e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 2.4819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3030 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 186/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 2.1999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.0020e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.0874e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.0612e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.0126e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.6196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.1591e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 8.7354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 8.3655e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 8.0357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 7.7440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 7.4799e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 7.2422e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 7.0271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 6.8310e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.6494e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.4819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.3270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.1832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 6.0488e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.9223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.8041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.6942e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.5910e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.4949e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.4042e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.3192e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.2431e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.1718e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.1050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.0420e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 4.9815e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 4.9232e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 4.8673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 4.8139e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 4.7623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 4.7126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 4.6648e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.6190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.5746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 4.5317e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.4903e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.4502e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.4112e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 4.3734e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.3368e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.3016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 4.2702e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.2396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.2099e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.1811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.1528e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.1252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.0983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.0721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.0464e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.0211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.9980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.9754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.9534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.9320e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.9111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.8908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.8708e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.8513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.8322e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.8135e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.7951e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.7769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.7592e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.7419e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.7248e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 3.7081e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 3.6917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 3.6757e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 3.6600e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.6444e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.6291e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.6140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.5992e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.5846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.5702e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.5562e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.5423e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.5287e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.5154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.5024e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.4896e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.4771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.4647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.4525e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.4405e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.4286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.4169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.4055e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.3942e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.3831e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.3722e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.3615e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.3509e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.3405e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.3302e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.3201e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.3101e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.3001e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.2903e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2807e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2712e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2436e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2346e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.2169e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.2082e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.1996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.1910e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.1825e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.1742e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.1659e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 2.1830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3083 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 187/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.7309e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 1.7194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.7440e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.7176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.7109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.7005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.6927e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.6832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.6565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6479e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.6391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.6340e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.6300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6233e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.6190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.6153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.6116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.6070e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.6023e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.5980e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.5945e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.5907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.5873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.5842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.5813e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.5780e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.5750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.5725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.5703e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.5678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.5650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.5627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.5606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.5587e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.5572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.5559e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.5547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.5594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.5634e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.5672e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.5709e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.5741e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.5768e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.5793e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.5817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.5839e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.5860e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.5880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.5900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.5916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.5929e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.5941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.5952e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.5961e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.5968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.5974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.5982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.5987e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.5993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.5999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.6004e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.6008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.6011e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.6014e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.6016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.6017e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.6016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.6016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.6016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.6016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.6016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.6016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.6015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.6015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.6015e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.6013e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.6012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.6010e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.6007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.6004e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.6001e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.5999e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.5996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.5993e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.5990e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.5987e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.5983e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.5978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.5974e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.5969e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.5964e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.5958e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.5953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.5947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.5941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.5936e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.5931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5913e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.5907e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.5901e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.5894e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.5887e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5880e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5860e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5853e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5847e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5840e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5833e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5804e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5797e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5789e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.4916e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3127 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 188/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.3808e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 1.5221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.5274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 1.5479e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.5386e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.5217e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.5034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.4821e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.4602e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.4415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.4274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.4134e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.4028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.3932e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.3846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.3754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.3663e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.3593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.3529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.3463e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.3396e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.3335e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.3286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.3236e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.3191e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.3153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.3119e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.3081e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.3043e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.3005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.2968e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.2931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.2893e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.2857e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.2828e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.2798e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.2771e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.2749e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.2732e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.2713e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.2699e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.2686e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.2673e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.2659e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.2645e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2606e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.2584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.2574e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.2563e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.2552e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.2541e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.2534e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.2526e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.2517e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.2508e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.2500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.2491e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.2483e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.2475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2467e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2459e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2450e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2442e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.2435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.2427e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.2417e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2409e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2400e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.2391e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2375e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2367e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.2360e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2344e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2328e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2319e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2311e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2303e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2286e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2271e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2266e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2245e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2234e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2223e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2207e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2201e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2195e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2184e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2171e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2165e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2153e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2142e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2136e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2129e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2123e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2117e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2092e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2086e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.1355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3173 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 189/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.1089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.0841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0786e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.0608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.0349e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.0262e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.0253e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.0226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.0236e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.0230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.0250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.0270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.0294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.0299e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.0296e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.0287e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.0281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.0273e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.0257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.0245e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.0237e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.0230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.0227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.0226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.0229e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.0228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.0226e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.0225e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.0222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.0218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.0212e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.0207e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.0202e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.0198e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.0196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.0194e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.0193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.0190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.0185e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.0181e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.0176e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.0172e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.0166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.0160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.0155e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.0150e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.0145e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.0140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.0136e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.0130e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.0124e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.0117e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.0111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.0105e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.0097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.0090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.0084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.0077e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.0070e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.0063e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.0057e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.0051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.0045e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.0039e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.0032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.0025e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.0018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.0012e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.0006e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.0001e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.9962e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.9917e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.9874e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.9830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.9807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.9779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.9750e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.9732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.9709e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.9683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.9661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.9636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.9611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.9585e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.9562e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.9537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.9534e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.9531e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.9525e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.9515e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.9501e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.9485e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.9470e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.9453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.9436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 9.9419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 9.9402e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 9.9384e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 9.9363e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 9.9352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 9.9338e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 9.9375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 9.9410e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 9.9442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 9.9475e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 9.9505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 9.9535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 9.9563e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 9.9589e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 9.9613e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 9.9635e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 9.9654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 9.9672e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 9.9688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 9.9703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 9.9717e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 9.9730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 9.9741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 1.0104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3208 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 190/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.1257e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.0913e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0658e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0284e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 9.9839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.0004e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 9.9744e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 9.8916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 9.7837e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 9.7007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 9.6484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 9.5925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 9.5512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 9.5188e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 9.5025e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 9.4774e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 9.4521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 9.4277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.4042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.3751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 9.3421e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.3126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 9.2882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 9.2660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 9.2474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 9.2302e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 9.2159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - 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9.0925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.0824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.0734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.0647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 9.0570e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 9.0477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 9.0380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 9.0282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 9.0195e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 9.0098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 9.0210e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 9.0314e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 9.0412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 9.0493e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 9.0572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 9.0647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 9.0721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 9.0783e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 9.0839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 9.0891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 9.0936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 9.2057e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 9.9123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 9.9813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.0047e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.0109e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.0167e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.0222e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.0275e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.0325e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.0373e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.0419e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.0463e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.0506e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.0547e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.0586e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.0623e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.0659e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.0692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.0724e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.0754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.0783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.0811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.0838e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.0864e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.0888e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.0912e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.0935e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.0957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.0978e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.0998e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.1016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.1034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.1051e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.1067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.1083e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.1098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.1113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.1127e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.1140e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.1154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.1166e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.1178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.1190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.1200e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.1211e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.1220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.1230e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.1238e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.1247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.1255e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.1263e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.1270e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.1277e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.1284e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.1290e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.1295e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.1301e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.1306e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 1.1908e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3226 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 191/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.0128e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 9.9769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0159e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0443e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0439e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.0374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0281e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.0032e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.9183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.8389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.7592e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 9.6851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 9.6163e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 9.5617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.5004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.4388e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 9.3805e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.3249e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.2671e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.2065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.1500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.1019e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 9.0539e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 9.0154e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 8.9816e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 8.9508e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 8.9198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 8.8895e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 8.8619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 8.8354e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 8.8107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 8.7847e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 8.7598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 8.7378e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 8.7163e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 8.6995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 8.6838e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 8.6700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 8.6556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 8.6425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 8.6291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 8.6166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 8.6043e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 8.5911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 8.5786e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 8.5803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 8.5809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 8.5831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 8.5851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 8.5865e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 8.5868e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.5861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.5844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.5828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.5805e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.5782e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.5755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.5732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.5702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.5672e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 8.5640e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.5610e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.5575e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.5537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 8.5503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.5466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.5423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 8.5374e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 8.5325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 8.5279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 8.5230e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.5187e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.5144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.5103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.5068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 8.5030e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 8.4993e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 8.4955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 8.4913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 8.4869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 8.4822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 8.4777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 8.4730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 8.4695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 8.4659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 8.4627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 8.4594e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 8.4559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.4527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.4495e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.4460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 8.4422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 8.4385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 8.4348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 8.4312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.4282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.4253e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 8.4224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.4193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.4159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.4125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 8.4089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.4051e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.4012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 8.3973e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.3934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.3894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 8.3854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.3817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.3780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.3742e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 8.3703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.3663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.3636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 8.3608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.3577e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.3546e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.3516e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 8.3487e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 8.0022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3252 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 192/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 7.4898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 7.3181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.3484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.2080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.0830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.0026e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.9712e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.9306e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.9143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.9071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.9047e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.8926e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.8940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.9264e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.9585e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.9779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.9923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.0025e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.0094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.0117e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.0089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.0074e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.0085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.0067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.0057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.0063e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.0086e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.0083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.0067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.0043e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.0021e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.9581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.9561e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.9540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.9515e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.9483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.9450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.9421e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.8876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.8850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.8824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.8796e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.8769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.8742e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.8717e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.8690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.8663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.8636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.8608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.8579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.8548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.8519e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.8489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.8458e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.8428e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.8404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.8382e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.8357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.8333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.8307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.8281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.8264e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.8245e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.8228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.8213e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.8197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.8180e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.8163e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.8146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.8128e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.8111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.8092e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.8074e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.8056e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.8038e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.8019e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.8002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.7983e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 6.5811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3289 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 193/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 6.3560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 6.4186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.4128e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 6.2991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.1988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.1420e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.1000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.0671e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 6.0208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 5.9904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 5.9812e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 5.9785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.9808e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.9832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 5.9874e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.9826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.9804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.9767e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 5.9702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 5.9612e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 5.9494e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 5.9419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 5.9385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 5.9332e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 5.9287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.9262e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.9243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.9205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.9160e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.9258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.9333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.9389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.9419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.9442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.9488e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.9521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.9560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.9596e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.9628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.9650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.9672e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 5.9686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 5.9696e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 5.9693e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 5.9680e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 5.9668e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 5.9663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 5.9654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 5.9647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 5.9638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 5.9634e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 5.9624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.9655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.9695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.9736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.9770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.9797e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.9820e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.9841e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.9857e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.9874e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.9892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.9909e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.9927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.9942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.9954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.9962e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.9965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.9963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 5.9958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 5.9955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 5.9949e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 5.9942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 5.9936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 5.9930e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 5.9924e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.9916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 5.9940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 5.9964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 5.9984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 5.9999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.0015e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.0030e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.0042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.0056e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 6.0150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.0239e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.0325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 6.0408e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.0486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.0561e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 6.0631e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.0698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.0764e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.0829e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 6.0892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 6.0953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 6.1013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.1073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.1131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.1186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.1240e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.1293e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.1342e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.1388e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.1432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.1475e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.1517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.1559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.1600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.1643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.1683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.1724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.1765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.1805e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.1842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.1882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.1921e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.1959e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.1995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 6.6298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3291 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 194/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 9.4508e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 8.5898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 8.3087e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 8.0718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 7.8561e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 7.7150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 7.6089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 7.4873e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 7.3582e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 7.2554e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 7.1881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 7.1215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 7.0688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 7.0358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 7.0191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 7.0034e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 6.9803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 6.9600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.9388e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.9154e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.8878e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.8601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.8364e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.8126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.7912e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.7750e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.7617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.7475e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.7323e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.7174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.7033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.6883e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 6.6721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 6.6558e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 6.6522e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 6.6474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 6.6431e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 6.6389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.6350e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.6299e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.6240e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 6.6175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.6113e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.6044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.5967e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.5896e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.5830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.5759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.5706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.5650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.5602e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 6.5552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.5500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.5447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 6.5392e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.5340e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.5283e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.5224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 6.5171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.5115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.5060e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 6.5005e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.4954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.4903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 6.4850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.4798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.4744e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.4687e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 6.4627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.4569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.4514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 6.4457e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.4403e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.4352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 6.4301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.4247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.4193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.4139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 6.4085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.4033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.3979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 6.3925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.3873e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.3819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.3767e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 6.3716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.3667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.3617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 6.3567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.3517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.3472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.3426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.3380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.3335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.3291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.3245e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.3202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.3159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.3116e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.3072e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.3028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2983e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.2939e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2848e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.2802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2712e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.2668e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.2624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.2581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.2536e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.2492e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.2453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.2413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.2373e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.2332e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.2292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.2252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.2212e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 5.7450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3324 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 195/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 4.8621e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 5.0344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.1936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 5.1481e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 5.0978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 5.1835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 5.2725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 5.3003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 5.3009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 5.2957e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 5.2972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 5.2942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.2932e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.2913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 5.2882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.2803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.2688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 5.2601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 5.2503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.2398e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 5.2276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 5.2180e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.2110e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.2023e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 5.2079e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 5.2125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.2159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 5.2172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.2177e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 5.2169e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.2158e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 5.2133e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.2097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.2069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.2046e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.2017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.1992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.1964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.1941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.4209e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.6306e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.8251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.0055e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.1742e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 6.3311e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 6.4774e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 7.3560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 7.4382e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 7.5150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 7.5865e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 7.6539e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 7.7178e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 7.7776e-07 - 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0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 8.6303e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 8.6407e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 8.6505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 8.6597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 8.6683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 8.6762e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 8.6835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 8.6903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 8.6964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 8.7020e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 8.7071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 8.7120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 8.7165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 8.7207e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 8.7247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 8.7284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 8.7316e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 8.7345e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 8.7372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 8.7395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 8.7415e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 8.7431e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 8.7445e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 8.7458e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 8.7468e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 8.8725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3282 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 196/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 6.8064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 6.9729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 6.8564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 6.6804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 6.6508e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 6.6034e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 6.5523e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.4794e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.4100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.3521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 6.3232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.2950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.2793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 6.2670e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.2542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.2394e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.2235e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 6.2047e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.1849e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.1647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 6.1447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.1295e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.1178e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.1050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 6.0941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.0837e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.0741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 6.0636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.0526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.0409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.0316e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 6.0220e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 6.0108e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 6.0039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 5.9986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 5.9940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.9898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.9857e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 5.9815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 5.9761e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 5.9704e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 5.9643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.9579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.9517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 5.9449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.9383e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.9321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.9260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 5.9201e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.9144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.9097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 5.9044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8930e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 5.8807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.8743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.8681e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 5.8621e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.8560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.8500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 5.8442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.8390e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.8338e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.8284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 5.8232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.8182e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.8131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 5.8077e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.8024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.7973e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 5.7922e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.7872e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.7824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.7778e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 5.7730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.7682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.7635e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.7587e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.7538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.7487e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.7437e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.7389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.7343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.7298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.7253e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.7210e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.7165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.7120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.7074e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.7039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.7004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.6969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.6933e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.6899e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.6864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.6830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.6797e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.6764e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.6729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.6695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.6664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.6633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.6601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.6568e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.6536e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.6504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.6472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.6442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.6413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.6385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.6357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.6327e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.6298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.6268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 5.6238e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.6207e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.6178e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.6149e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 5.6121e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 5.2725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3314 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 197/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 302ms/step - accuracy: 1.0000 - loss: 4.3224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 4.4753e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.5364e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.5126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.4669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.4243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.4065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.3799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 4.3478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.3258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.3239e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.3274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.3344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.3443e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.3513e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.3557e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3671e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3766e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3821e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3853e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.3868e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.3877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.3888e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.3914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.3970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - 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4.4082e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.4080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.4080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.4082e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.4085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.4079e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.4088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.4094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.4098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.4099e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.4094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.4090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.4090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.4090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.4099e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.4106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.4112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.4114e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.4112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.4107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.4101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.4091e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.3802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 4.3790e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.3777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.3761e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.3746e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.3733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.3719e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.3615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.3599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.3586e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.3573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.3560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.3548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.3537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.3526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.3515e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.3502e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.3489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.3479e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.3468e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.3458e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.3447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.3437e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.3426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.3416e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.3406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.3398e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.3388e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.3377e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.3367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.3356e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.3344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.3332e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.3321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.3309e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.3298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 4.1975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3353 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 198/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 4.1016e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 4.0512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.1291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 4.1164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.0661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.0345e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.9937e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.9639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.9276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.9007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.9312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 3.9534e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.9722e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 3.9915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.0111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.0261e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.0374e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.0456e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.0578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.0739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.0854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.0951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.1037e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.1100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.1155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.1202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.1241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.1281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.1311e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.1336e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.1353e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.1364e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.1365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.1361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.1367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.1363e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.1448e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.1527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.1599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.1667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.1723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.1777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.1822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.1856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.1880e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.1900e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.1920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.1935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.1953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.1970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.1985e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.1994e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2008e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2001e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.1995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.1989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.1986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.1982e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.1974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.1966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.1957e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.1948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.1937e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.1927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.1916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.1903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 4.1890e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 4.1876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 4.1861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.1850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.1837e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.1824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.1811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.1797e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.1784e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.1770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.1756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.1741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.1725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 4.1748e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 4.1770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 4.1790e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 4.1807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 4.1824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 4.1840e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 4.1854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 4.1868e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 4.1881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 4.1894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.1904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.1914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.1923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 4.1933e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.1941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.1949e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.1956e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.1963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.1970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 4.1976e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.1981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.1987e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.1992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 4.1996e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.1999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.2004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 4.2008e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.2011e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.2014e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.2016e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 4.2018e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 4.2158e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3366 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 199/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.9691e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.8725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.8707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.8231e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.7843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.7395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.6916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.6471e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.6043e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.5805e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 3.5697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 3.5561e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 3.5533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.5560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.5615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.5622e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 3.6869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 3.6910e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.6951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.6988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 3.7025e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.7060e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.7095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.7129e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 1.0000 - loss: 3.7160e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.7190e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.7218e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 3.7244e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.7267e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.7289e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.7311e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 3.7332e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.7352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.7372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 3.7395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.7418e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.7439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.7459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 1.0000 - loss: 3.7483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 3.7505e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 3.7525e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 3.7545e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 3.7564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 3.7581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 3.7599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.7615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.7631e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.7647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.7660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 3.7675e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 3.7688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 3.7702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 3.7715e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 3.7727e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 3.7739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 3.7751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 3.9100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3400 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 200/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.4818e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.6155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 3.6881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.6319e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.5698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.5313e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.5045e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 3.4721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 3.4504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 3.4411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 3.4334e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 3.4234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 3.4209e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.4182e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.4162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.4122e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 3.4065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.4009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.3961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.3913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 3.3843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.3796e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.3808e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 3.3820e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.3830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 3.3845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 3.3862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 3.3864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 3.3858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 3.3852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 3.3842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.3825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.3800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.3778e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 3.3758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.3737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.3719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.3702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.3686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.3663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.3639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 3.3615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.3590e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.3563e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.3532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.3503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.3477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 3.3449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.3422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.3397e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.3372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 3.3344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.3316e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.3286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 3.3255e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.3224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.3191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.3159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 3.3128e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.3095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.3064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 3.3034e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.3006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.2978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 3.2948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2918e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 3.2832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.2804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.2777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 3.2753e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 3.2731e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 3.2709e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 3.2689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2623e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.2602e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2555e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.2533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2488e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2465e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.2446e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2427e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2408e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2391e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.2374e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.2357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.2338e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.2321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.2304e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.2289e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.2274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.2260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.2247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.2234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.2225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.2219e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.2213e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.2208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.2202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.2196e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.2189e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2184e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2177e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 3.2171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 3.2151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.2145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.2141e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.2136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.2131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.2125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.2120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.2116e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 3.1594e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3432 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 201/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 3.1577e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 3.4369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 3.7025e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.7138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.6661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.6287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 3.5801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 3.5259e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 3.4698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 3.4243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 3.3979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.3727e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.3528e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 3.3352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 3.3203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 3.5267e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 3.6950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 3.8416e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 3.9629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.0625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 4.1438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 4.2127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 4.2723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.3297e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.3800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.4236e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.4605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.4906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.5153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.5363e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.5535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.5668e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.5766e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.5842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.5906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.5951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.5982e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.6006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.6023e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.6022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.6010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.5990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.5959e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.5917e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.5865e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.5809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.5751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.5688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.5663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.5634e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.5601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.5563e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.5520e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.5474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.5426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.5384e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.5337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.5289e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.5242e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.5191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.5140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.5088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.5039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.4987e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.4932e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.4877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.4824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.4770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.4712e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.4652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.4594e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.4534e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.4477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.4423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.4369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.4315e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 4.4261e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 4.4206e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 4.4150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.4093e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.4036e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.3978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.3920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.3861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.3803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.3744e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.3689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.3632e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.3575e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.3519e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.3464e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.3409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.3352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.3296e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.3241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.3186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.3132e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.3081e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.3030e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.2979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.2927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.2875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.2823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.2770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.2717e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.2665e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.2613e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.2562e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.2512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.2462e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.2412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.2368e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.2324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.2280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.2236e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.2193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.2150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.2108e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.2065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.2023e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 3.6924e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3447 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 202/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.5572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 3.3823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.2764e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.1745e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.0941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.0385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.9954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.9513e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.9184e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.8941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.8815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.8688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.8464e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.8353e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.8262e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.8276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.8305e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.8324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.8335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.8355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.8371e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.8375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.8369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.8365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.8361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.8360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.8358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.8359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.8361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.8358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.8352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.8345e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.8337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.8323e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.8305e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.8290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.8277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.8262e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.8249e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.8241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.8233e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.8224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.8215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.8206e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.8197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.8194e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.8187e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.8181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.8176e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.8172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.8167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.8162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.8158e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.8152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.8146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.8140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.8133e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.8125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.8115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.8105e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.8095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.8084e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.8074e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.8065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.8056e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.8048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.8040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.8031e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.8023e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.8013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.8003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.7992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.7982e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.7970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.7960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.7950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.7940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.7930e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.7919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.7908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.7897e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.7887e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.7876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.7864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.7854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.7843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.7834e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.7825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.7817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.7809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.7800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.7792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.7783e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.7774e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.7764e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.7754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.7745e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.7734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.7725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.7715e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.7706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.7696e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.7687e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.7678e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.7669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.7659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.7649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.7638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.7629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.7620e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 2.6560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3474 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 203/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 2.7600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.7905e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 2.7527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 2.7533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.7286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 2.7722e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 2.7875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 2.7878e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.7768e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.7726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.7751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.7711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.7652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.7597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.7554e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.7537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.7487e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.7447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.7395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.7354e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.7309e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.7260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.7220e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.7206e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.7217e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.7226e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.7241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.7248e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 2.7246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 2.7242e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 2.7237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 2.7225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 2.7205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 2.7188e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 2.7172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 2.7158e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 2.7145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 2.7130e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 2.7113e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 2.7091e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 2.7067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 2.7049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 2.7031e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 2.7011e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 2.6986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 2.6961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 2.6936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 2.6908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.6887e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.6867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.6849e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.6827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.6804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.6780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.6756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.6760e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.6761e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.6759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.6758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.6756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.6754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.6751e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.6748e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.6743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.6736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.6727e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.6719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.6708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.6697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 2.6688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.6680e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 2.6672e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.6666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.6660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.6654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.6647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.6638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.6632e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.6624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 2.6617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 2.6608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 2.6599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 2.6591e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 2.6582e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 2.6574e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 2.6566e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 2.6557e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 2.6548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 2.6539e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 2.6528e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 2.6518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 2.6507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 2.6496e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 2.6484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 2.6473e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 2.6461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 2.6451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 2.6441e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 2.6432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 2.6422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 2.6412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 2.6401e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 2.6391e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 2.6381e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 2.6371e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 2.6360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 2.6352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 2.6343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 2.6334e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 2.6326e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 2.6318e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 2.6310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 2.6301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 2.6292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 2.6283e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 2.6273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.6262e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.6252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.6242e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.6232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 2.5017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3502 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 204/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 2.6522e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.6249e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.5920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.5441e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.4903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.4362e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.3927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 2.3477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.3068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 2.2780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.2569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.2378e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 2.2258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 2.2164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 2.2096e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.2081e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.2057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.2024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 2.1994e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.1958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.1911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.1862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.1823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.1788e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.1765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.1756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 2.1749e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.1968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.1965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1967e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.1969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.1969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.1968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.1967e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.1966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.1965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.1964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.1963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.1962e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.1961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.1960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.1958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.1956e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.1954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.1953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.1950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.1948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.1945e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.1942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 2.1576e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3525 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 205/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 302ms/step - accuracy: 1.0000 - loss: 2.0965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.0605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.1536e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.1716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 2.1543e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.1342e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.1152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.0961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.0730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.0545e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.0422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.0331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.0275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.0234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.0213e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.0175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.0129e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.0079e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.0029e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.9977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.9943e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.9918e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.9902e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.9886e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.9881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9881e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.9885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.9884e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.9882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.9880e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.9874e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.9867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.9859e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.9853e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.9842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.9832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.9822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.9814e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.9806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.9794e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.9782e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.9771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.9758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.9743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.9728e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.9716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.9705e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.9694e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.9684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.9676e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.9667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.9658e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.9649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.9640e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.9630e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.9619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.9610e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.9603e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.9603e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.9604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.9605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.9606e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.9605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.9605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.9604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.9603e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.9601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.9599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.9599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.9608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.9618e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.9628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.9636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.9645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.9652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.9659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.9665e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.9725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.9782e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.9836e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.9889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.9942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.9992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.0040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.0088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.0135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.0180e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.0223e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.0265e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.0305e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.0343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.0380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.0416e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.0452e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.0486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.0520e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.0553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.0593e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.0630e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.0666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.0702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.0736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.0768e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.0800e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.0831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.0863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.0892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.0922e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.0950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.0978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.1006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.1032e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.1057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.1083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.1107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.1130e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.1153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.1175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.1197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 2.3805e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3552 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 206/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.0995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 2.1036e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.1754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.1803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.6699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.0391e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.0363e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1103e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1495e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1691e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.1762e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1710e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.1520e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1397e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1263e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.1122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0977e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0841e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0703e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0567e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0434e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0303e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 9.3939e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.2936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.1970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.1033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 9.0123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.9241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.8384e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.7551e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.6737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.5954e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.5190e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.4450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.3726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.3015e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.2322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.1651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.0995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.0355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 7.9739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 7.9139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 7.8551e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.7975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.7412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.6861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.6320e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.5791e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.5275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.4771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.4278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.3798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.3331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.2874e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.2428e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.1990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 7.1559e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.5991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.5671e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.5357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.5048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.4745e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.4447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.4155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.3866e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.3582e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.3302e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.3027e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.2755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.2486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.2221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.1961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.1704e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.1451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.1203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.0958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0242e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.0010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.9780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.9553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.9329e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.9109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.8891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.8677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.8466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.8258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.8053e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.7851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 5.7650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 5.7453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 5.7257e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.7064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.6873e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.6685e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 5.6499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 3.4390e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3532 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 207/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.5667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.5457e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.5127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.4596e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.4010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.3824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.3727e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.3597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.3423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.3296e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.3208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.3089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.3109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.3164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.3206e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3311e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.3347e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.3312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.3287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.3269e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.3248e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.3227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.3208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.3185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.3167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.3151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.3135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.3120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.3097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.3065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.3033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.3004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.2972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.2943e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.2916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.2900e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.2879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.2856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.2833e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.2810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.2785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.2759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.2732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.2706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.2679e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.2655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.2633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 2.2613e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.2591e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.2567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.2544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 2.2521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.2499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.2476e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.2453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.2431e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.2409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.2388e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.2367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.2348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.2327e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.2306e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.2285e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.2265e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.2244e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.2223e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.2202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.2182e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.2162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.2144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.2125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.2109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.2093e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.2076e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.2060e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.2044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.2029e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.2012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.1996e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.1981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.1966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.1951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.1936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.1922e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.1907e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.1892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.1879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.1865e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.1852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.1839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.1825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.1812e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.1799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.1787e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.1776e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.1766e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.1756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.1746e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.1736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.1726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.1717e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.1707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.1697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.1688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.1679e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.1670e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.1661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.1652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.1643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.1633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.1624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.1614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.1605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.1596e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.1587e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.1579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.1570e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 2.0553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3556 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 208/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.1012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.0064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 1.9647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 1.9151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.8893e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.8741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.8577e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.8484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.8378e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.8321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.8282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.8247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.8215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.8204e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.8192e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.8171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.8147e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.8121e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.8090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.8058e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.8090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.8114e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.8145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.8168e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.8188e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.8203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.8227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.8252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.8269e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.8281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.8292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.8298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.8302e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.8307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.8312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.8314e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.8317e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 1.8322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.8358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.8399e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 1.8435e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.8468e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.8499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.8525e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 1.8546e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.8569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 1.8591e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.8611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.8628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.8644e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.8660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.8672e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.8682e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.8690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.8697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.8702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.8705e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.8709e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.8712e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.8715e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.8720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.8724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.8729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.8732e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.8734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.8734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.8734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.8737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.8737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.8737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.8738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.8737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.8736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.8735e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.8734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.8733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.8730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.8727e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.8723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.8791e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.8855e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.8917e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.8977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.9034e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.9090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.9143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.9195e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.9244e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.9291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.9337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.9381e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.9423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.9463e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.9503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.9541e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.9578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.9615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.9651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.9686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.9720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.9752e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.9783e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.9812e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.9841e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.9868e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.9894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.9920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.9945e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.9968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.9991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 2.0013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 2.0035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 2.0055e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 2.0075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 2.0095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 2.0113e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.0131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.0148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.0165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.0181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 2.2104e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3582 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 209/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 2.0957e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 2.1769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 1.0000 - loss: 2.1893e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.1440e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.1092e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.0879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 2.0639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.0433e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.0170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.9960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.9850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.9724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.9627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.9540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.9469e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.9386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.9301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.9218e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.9147e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.9070e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.9002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.8947e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.8911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.8875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.8842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.8814e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.8839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.8856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.8862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.8867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.8872e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.8873e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.8866e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.8858e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.8853e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.8845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.8838e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.8832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.8832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8814e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8794e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8788e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.8783e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.8779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.8773e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.8765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.8756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.8745e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.8734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.8723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.8711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.8699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.8688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.8677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.8667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.8657e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.8646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.8636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.8625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.8615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.8604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.8593e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.8583e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.8572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.8562e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.8552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.8542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.8532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.8523e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.8513e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.8502e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.8491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.8480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.8468e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.8456e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.8444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.8432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.8420e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.8407e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.8395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8383e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8370e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.8358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.8346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.8333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.8321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.8308e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.8296e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.8284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.8271e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.8258e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.8246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.8234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8210e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.8186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.8173e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.8161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.8148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.8135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.8122e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 1.8109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 1.8062e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8050e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 1.8028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8016e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.8005e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.7994e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 1.7982e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 1.6650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3601 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 210/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 2.6540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.3639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.2274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.1130e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.0292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 1.9693e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 300ms/step - accuracy: 1.0000 - loss: 1.9402e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.9097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 1.8793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.8552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.8355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 1.8152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.8000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.7869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.7743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 1.7638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 1.0000 - loss: 1.7532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.7429e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.7330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.7230e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.7127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.7039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.6965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.6891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.6828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.6772e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.6722e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.6669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.6616e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.6477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.6427e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.6379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.6336e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.6293e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.6254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.6217e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.6183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.6152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.6121e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 1.6091e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.6061e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.6031e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.6001e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 1.5970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 1.5890e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 1.5823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5760e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 1.5741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 1.5683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 1.5636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5624e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 1.5601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5592e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 1.5587e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5582e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5575e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 1.5572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5568e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 1.5561e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5551e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 1.5549e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5546e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 1.5572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5584e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5596e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 1.5608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.5619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.5633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 1.5647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5675e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 1.5700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.5712e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.5723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 1.5734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.5745e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.5755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 1.5765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.5775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.5785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.5793e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 1.5802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.5810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 1.5817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.5824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5838e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.5844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5874e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.5884e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.5913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5922e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5930e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5938e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.5946e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.6846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3624 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 211/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.2744e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.3069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.3234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.3149e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.3012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.2925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.2892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.2802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.2703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.2625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.2586e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.2550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.2548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.2587e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.2628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.2665e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.2699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.2727e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.2749e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.2757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.2759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.2766e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.2777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.2785e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.2796e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.2815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.2835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - 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1.3009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.3026e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.3044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.3060e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.3076e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.3089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.3101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.3115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.3127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.3139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.3151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.3161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.3172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.3185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.3196e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 1.3322e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 1.0000 - loss: 1.3331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.3344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.3355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.3366e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 1.0000 - loss: 1.3375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.3384e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.3393e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 1.0000 - loss: 1.3403e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.3411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.3420e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 1.0000 - loss: 1.3429e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.3437e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.3445e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.3452e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 1.0000 - loss: 1.3460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.3467e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.3473e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 1.0000 - loss: 1.3478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.3483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 1.0000 - loss: 1.3488e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 294ms/step - accuracy: 1.0000 - loss: 1.3518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.3521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.3524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.3527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 1.0000 - loss: 1.3529e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.3532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 1.0000 - loss: 1.3535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.3537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.3540e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.3547e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.3553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.3560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.3566e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.3573e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.3578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.3584e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.3590e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.3595e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.3600e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.3605e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.3610e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.3614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.3625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.3636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.3646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.3655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.3664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.3673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.3683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 1.4801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3647 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 212/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.3688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.3188e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.3030e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.2853e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.2625e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.2422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.2293e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.2203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.2099e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.2098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.2138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.2155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2168e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.2183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2173e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.2157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.2107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.2093e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.2079e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.2082e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.2085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.2087e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.2093e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.2098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2108e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2110e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2113e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.2115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.2119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.2124e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.2129e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.2134e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.2136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.2138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.2140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.2139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.2138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.2136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.2139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.2141e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.2158e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.2175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.2192e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.2208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.2222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.2234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.2246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.2256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.2263e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.2270e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.2278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.2284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.2291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.2297e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.2304e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.2310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.2315e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.2319e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.2323e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.2326e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.2328e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.2330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.2333e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.2336e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.2339e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.2341e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.2344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.2346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.2348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.2349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.2350e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.2351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.2351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.2351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2354e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.2357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.2359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.2360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2360e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.2358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.2358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.2358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.2357e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.2356e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.2356e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.2355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2353e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.2352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2350e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2347e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2341e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2340e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2338e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2336e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.2190e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3668 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 213/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 1.3339e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.2993e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.3325e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.3475e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.3362e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3253e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.3166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.3126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.3136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.3136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.3154e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.3150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.3135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.3127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.3114e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.3105e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.3083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.3058e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.3044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.3030e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.3019e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.3008e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.2995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.2981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.2963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2943e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.2906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2865e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.2848e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.2841e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.2840e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.2841e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2841e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.2838e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.2835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.2832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.2828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.2824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.2819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.2813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.2806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.2798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.2791e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.2784e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.2776e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.2770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.2762e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2747e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.2730e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2587e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2577e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2557e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.2535e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.2527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.2519e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2511e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.2496e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2482e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.2467e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2453e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2446e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2418e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2396e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2382e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2362e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2348e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2341e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2334e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2327e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2320e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2314e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.2301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.1537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3693 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 214/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 1.2802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.2165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.1940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.1585e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.1263e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.1024e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.0898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.0768e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.0643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.0578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.0539e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.0510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.0491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.0521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.0549e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.0565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.0567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.0562e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 1.0556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 1.0544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 1.0850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 1.0000 - loss: 1.1116e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.1351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.1552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.1728e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.1884e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.2023e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.2150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.2261e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.2358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.2444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.2518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.2581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.2639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.2692e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.2737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.2779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.2823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.2861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.2896e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.2924e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.2951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.2974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.2994e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.3012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.3027e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.3041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.3053e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.3064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.3075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.3085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.3092e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.3097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.3101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.3103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3104e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3102e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.3098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.3095e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.3093e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.3089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.3085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.3079e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.3073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.3067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.3061e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.3054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.3048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.3041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.3034e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.3028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.3021e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.3014e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.3007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.2983e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2976e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.2960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2945e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2937e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2929e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2921e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2883e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2859e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2819e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.2803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2795e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2787e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.2771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2763e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.2748e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2742e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.2724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2705e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2698e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2691e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2685e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2678e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.1904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3715 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 215/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.1041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.1421e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.1515e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.1299e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.1134e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.1254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.1282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.1236e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.1155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.1091e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.1105e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.1107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.1110e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.1114e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.1114e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.1098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 1.1098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 1.1111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.1119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.1122e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.1124e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.1122e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.1122e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.1116e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.1114e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.1112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.1111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.1106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.1102e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 1.1098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.1094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.1091e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.1085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.1106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 1.1126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.1144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.1161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 1.1176e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.1189e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.1200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.1207e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 1.1213e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.1216e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.1219e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.1230e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.1239e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.1248e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.1256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.1264e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.1271e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.1277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.1283e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.1287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.1291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.1294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.1296e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.1296e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.1295e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.1293e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.1290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.1288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.1286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.1284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.1282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.1280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.1278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.1275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.1277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.1278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.1278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.1279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.1278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.1277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.1277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.1276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.1275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.1273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.1271e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.1269e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.1266e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.1263e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.1260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.1257e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.1253e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.1250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.1246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.1243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.1240e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.1237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.1234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.1230e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.1226e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.1223e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.1219e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.1215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.1211e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.1207e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.1203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.1199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.1195e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.1191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.1187e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.1182e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.1178e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.1173e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.1168e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.1164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.1159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.1154e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1130e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1125e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1115e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1110e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1106e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.0506e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3738 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 216/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 9.4798e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 9.3337e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 9.1950e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 8.9993e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 9.1385e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.1780e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.1488e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.1283e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 9.0827e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 9.0302e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 8.9982e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 8.9826e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.9678e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.9553e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 8.9504e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.9385e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.9206e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.9085e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 8.8974e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.8851e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.8682e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 8.8558e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.8463e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.8383e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.8391e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 8.8408e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.8462e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.8470e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 8.8475e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.8459e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.8451e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 8.8451e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.8433e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.8410e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.8393e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 8.8361e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.8346e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.8349e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 8.8362e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.8363e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.8349e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 8.8345e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.8341e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.8346e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.8336e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 8.8325e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.8321e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.8308e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 8.8303e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.8325e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.8344e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 8.8361e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.8369e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.8369e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.8368e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 8.8361e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 8.8348e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 8.8335e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 8.8329e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 8.8318e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 8.8319e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 8.8329e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 8.8337e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 8.8990e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 8.9611e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 9.0204e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.0767e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.1319e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 9.1839e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.2335e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.2812e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 9.3266e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.3706e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.4130e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.4539e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 9.4930e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.5307e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.5669e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 9.6053e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 9.6420e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 9.6767e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.7100e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 9.7427e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.7739e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.8044e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 9.8339e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.8626e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.8903e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 9.9169e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 9.9429e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.9700e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.9959e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0021e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0133e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0154e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0194e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0213e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0231e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0303e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0320e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0336e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0368e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0383e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0398e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.0484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.0569e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.0652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.0733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.0813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.0891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.0966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.9989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3703 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 217/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 2.5597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.2527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 2.1053e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.9878e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.9000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.8295e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.7735e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.7259e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 1.6815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6448e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.6191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.5990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.5817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 1.5667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.5530e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.5404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.5280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.5195e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.5121e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.5041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.4955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.4879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.4821e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.4762e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 1.4718e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.4678e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.4651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 1.4619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.4639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.4656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.4668e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.4675e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.4675e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.4674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.4677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.4676e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.4676e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.4674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.4673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.4669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.4669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.4666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.4663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.4656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.4647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.4637e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.4628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.4617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.4606e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.4595e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.4586e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.4576e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.4565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.4553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.4542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.4529e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.4514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.4500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.4488e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.4474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.4461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.4449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.4436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.4424e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.4412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.4398e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.4386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.4372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.4358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.4344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.4330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.4316e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.4301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.4287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.4274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.4260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.4245e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.4231e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.4217e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.4203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.4188e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.4174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4147e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4133e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.4107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.4094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.4087e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.4079e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.4073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.4065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.4057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.4049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.4042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 1.4035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.4027e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.4019e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.4012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.4004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.3996e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.3988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 1.3979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.3970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.3961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 1.3952e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.3943e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.3934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 1.3925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.3916e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.3907e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.3898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.3888e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.3879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.3870e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.3861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.3851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.3842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.3833e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 1.3823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 1.2701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3718 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 218/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 1.1244e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.1706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.1844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.1471e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.1370e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.1305e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.1235e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.1137e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.1077e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.1067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 1.1084e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.1118e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.1134e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 1.1146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.1147e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.1146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.1149e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.1145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.1141e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.1159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.1175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.1189e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.1198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.1205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.1223e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.1236e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 1.1242e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 1.1246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.1256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.1267e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.1274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.1275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.1277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.1280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.1280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.1282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.1283e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.1284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.1286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.1288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.1289e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.1290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.1288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 1.1286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.1283e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.1281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 1.1276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.1278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.1279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.1280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 1.1279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.1277e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.1276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 1.1274e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.1272e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.1268e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.1264e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 1.1260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.1257e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.1254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 1.1250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.1247e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.1243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 1.1238e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.1233e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.1228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.1222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 1.1215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.1208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.1201e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 1.1194e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.1187e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.1181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 1.1174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.1171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.1168e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.1165e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 1.1161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.1157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.1153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 1.1148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.1143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.1138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.1133e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.1128e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.1123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.1118e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.1112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.1107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.1101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.1096e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.1090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.1085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.1080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.1075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.1071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.1066e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.1062e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.1058e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.1054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.1049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.1045e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.1041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.1037e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 1.0000 - loss: 1.1033e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.1029e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.1025e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 1.1021e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.1017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.1014e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.1010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 1.1010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.1010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.1010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.1010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.1010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.1009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 1.0000 - loss: 1.1009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.1008e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 1.0952e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3743 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 219/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 9.6508e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 9.8440e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 9.8097e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 9.5836e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 9.4948e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 9.4294e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.4340e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 9.4035e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 9.3541e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 9.3564e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 9.3577e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 9.3449e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 9.3364e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 9.3366e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 9.3402e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.3372e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.3304e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.3211e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 9.3199e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 9.3148e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 9.3101e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 9.3075e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 9.3247e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 9.3375e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 9.3474e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 9.3553e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 9.3638e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 9.4023e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 9.4353e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 9.4662e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 9.4915e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 9.5119e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 9.5278e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 9.5436e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 9.5584e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 9.5696e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 9.5796e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 9.5884e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 9.5970e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 9.6074e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 9.6149e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 9.6234e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 9.6301e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 9.6349e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 9.6390e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 9.6435e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 9.6486e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 9.6525e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 9.6572e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 9.6612e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 9.6644e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 9.6671e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 9.6697e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 9.6712e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 9.6728e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 9.6738e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 9.6739e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 9.6740e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 9.6741e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 9.6749e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 9.6764e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 9.6781e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 9.6796e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 9.6804e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 9.6805e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 9.6800e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 9.6793e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 9.6778e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 9.6757e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 9.6733e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 9.6716e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 9.6699e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.6684e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.6669e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 9.6655e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.6641e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.6625e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.6606e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 9.6594e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.6577e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.6556e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 9.6536e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.6519e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.6501e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.6485e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 9.6469e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.6450e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.6431e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 9.6409e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.6386e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.6362e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 9.6335e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.6307e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.6278e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.6250e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 9.6220e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.6188e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.6161e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 9.6135e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.6109e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.6085e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.6065e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 9.6042e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 9.6017e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 9.5990e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 9.5990e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 9.5990e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 9.5988e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 9.5984e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 9.5981e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 9.5976e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 9.5969e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 9.5960e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 9.5952e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 9.5942e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 9.5934e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 9.5923e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 9.5911e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 9.5899e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 9.5886e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 9.4305e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3766 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 220/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 8.8167e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 8.3644e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.0627e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 7.8463e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 7.7289e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 7.7648e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 7.7575e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 7.8513e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 7.8828e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 8.0229e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 8.2523e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 8.4237e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 8.5629e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 8.6734e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 8.7660e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.8289e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.8830e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.9286e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.9625e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.9866e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.9966e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 9.0207e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 9.0418e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 9.0584e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 9.0803e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 9.0998e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 9.1162e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 9.1293e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 9.1402e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 9.1504e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 9.1569e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 9.1607e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 9.1617e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 9.1625e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 9.1632e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.1619e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.1596e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 9.1566e-08 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 9.1722e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 9.1712e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 9.1700e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 9.1691e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 9.1680e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 9.1664e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 9.1659e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 9.1650e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 9.1637e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 9.1626e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.1612e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.1595e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.1576e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.1554e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.1528e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.1501e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.1475e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.1458e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.1438e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.1414e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.1386e-08 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.1553e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.1575e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.1597e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.1614e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.1636e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.1658e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 9.1680e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 9.1710e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 9.1737e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 9.1760e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 9.1785e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 9.1806e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 9.1822e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 9.1838e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 9.1854e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 9.1868e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 9.1882e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 9.1892e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 9.1940e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 9.2043e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 9.2142e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 9.2237e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 9.2328e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 9.2413e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 9.2491e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 9.2567e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 9.2643e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 9.2713e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 9.2781e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.2849e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.2915e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.2977e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.3035e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 9.3090e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 9.3142e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 9.3195e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 9.3243e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 9.3289e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 9.3332e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 9.3372e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 9.8161e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3785 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 221/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 9.2535e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 8.9753e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 8.9530e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.7976e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.6960e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.5716e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.5266e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.4478e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 8.3832e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 8.3251e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 8.2864e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.2397e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.2043e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 8.1771e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 8.1608e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 8.1356e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.1046e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.0804e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.0584e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.0344e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.0088e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 7.9920e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 7.9778e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 7.9623e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 7.9464e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 7.9339e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 7.9242e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 7.9134e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.9059e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.8990e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.8922e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.8842e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.8743e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.8656e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.8576e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.8488e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.8411e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.8334e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.8262e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.8188e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.8108e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 7.8024e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.7965e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.7909e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 7.7844e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 7.7778e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 7.7724e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 7.7675e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 7.7631e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 7.7591e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 7.7554e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 7.7510e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.7460e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.7411e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.7366e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.7330e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.7289e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.7251e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.7226e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.7198e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.7170e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.7142e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.7114e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.7104e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.7091e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.7094e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.7104e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.7112e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.7114e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.7134e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.7159e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.7182e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.7203e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.7237e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.7269e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.7295e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.7317e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.7342e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.7372e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.7399e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.7426e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.7453e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.7481e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.7509e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.7569e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.7627e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 7.7683e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 7.7824e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 7.7963e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.8096e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.8226e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.8351e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.8469e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.8583e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.8694e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.8800e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.8902e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.9001e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.9096e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.9188e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.9276e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.9360e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.9439e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.9513e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.9583e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.9649e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.9753e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.9854e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.9957e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.0057e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.0156e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.0249e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.0338e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.0424e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.0507e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.0585e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.0662e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.0737e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.0811e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.0881e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 8.9206e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.3792 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 222/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 7.0269e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 7.0898e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 7.2604e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.8618e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.3581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.5936e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 2.6999e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.7346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.7334e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 2.7182e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 2.6911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 2.6560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 2.6170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.5768e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.5369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.4974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.4579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.4208e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.3846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.3495e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.3152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.2827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.2518e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.2219e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.1937e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.1670e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.1413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.1164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.0923e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.0690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.0466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.0250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.0041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.9844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 1.9656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.9476e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.9301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.9134e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.8971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.8510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8367e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.8091e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.7959e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.7831e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.7708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.7588e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.7252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.7145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.7042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.6940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6748e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.6571e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6488e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6408e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.6330e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.6256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.6183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.6111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.6041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.5971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.5902e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.5835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.5769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.5704e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.5640e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.5578e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.5516e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.5456e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.5396e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.5337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.5279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.5223e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.5167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.5111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.5057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.5003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4899e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.4848e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.4798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.4748e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.4699e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.4651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.4603e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.4556e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.4510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.4464e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.4419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.4375e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.4331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.4289e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.4246e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.4205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.4163e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.4122e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.4082e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.4043e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.4003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.3964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.3926e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.3888e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.3850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.3813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.3777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.3742e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.3708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.3674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.3641e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.3609e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.3577e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.3545e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.3514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.3483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 9.8009e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.3796 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 223/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 8.2509e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 8.3637e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 8.4551e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 8.5117e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 8.4242e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 8.3182e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 8.1944e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 8.0917e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 7.9811e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 7.8861e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 7.9451e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 7.9871e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 8.0113e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 8.0259e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 8.0320e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 8.0329e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 8.0250e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 8.0158e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.0027e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 7.9873e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 7.9676e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 7.9482e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 7.9347e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 7.9172e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 7.8999e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 7.8851e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 7.8718e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 7.8657e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.8573e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.8486e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.8398e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 7.8314e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.8234e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.8154e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 7.8090e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.8025e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.7957e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.7903e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 7.7859e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.7806e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.7760e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.7718e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 7.7671e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 7.7616e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 7.7557e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 7.7505e-08 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.7171e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.7157e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 7.7133e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.7172e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.7205e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.7239e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.7264e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.7289e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.7323e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.7352e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.7372e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.7391e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.7406e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.7417e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.7435e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.7452e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.7467e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.7480e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.7488e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.7498e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.7511e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.7523e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.7530e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.7535e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.7536e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.7534e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.7533e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.7526e-08 - 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0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.7543e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.7542e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.7540e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.7537e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.7531e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.7524e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.7516e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 7.7508e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.7498e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.7485e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 7.7473e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.7462e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.7451e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 7.7439e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.7426e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.7419e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.7410e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 7.7400e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.7392e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.7383e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 7.7372e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.7359e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.7346e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.7340e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 7.7333e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 7.6509e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3824 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 224/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 36s 303ms/step - accuracy: 1.0000 - loss: 5.9161e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 6.6959e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.0093e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.9660e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.8898e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 6.8310e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.7726e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.7068e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.6456e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.6157e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.5939e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.5648e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.5360e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.5197e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.5040e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.4853e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.4645e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.4656e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.4662e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.4665e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.5008e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.5542e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.6011e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.6402e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.6762e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.7077e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.7387e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.7627e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.7822e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.7995e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.8132e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.8232e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.8423e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.8579e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.8720e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.8838e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.8951e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.9044e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.9138e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.9210e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.9264e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.9305e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9358e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9392e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9462e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9526e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.9593e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.9655e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.9734e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.9807e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.9877e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.9940e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.9992e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.0039e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.0076e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 7.0103e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.0123e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.0141e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 7.0156e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.0170e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.0179e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 7.0196e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.0211e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.0226e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.0234e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.0241e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.0244e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.0249e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.0248e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.0244e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.0240e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.0236e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.0236e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.0236e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.0233e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 7.0228e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.0223e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.0213e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 7.0202e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.0188e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.0171e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 7.0157e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.0142e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.0133e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.0124e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 7.0116e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 7.0107e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 7.0095e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 7.0081e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.0073e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.0064e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.0052e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 7.0040e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.0029e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.0019e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 7.0008e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 7.0000e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.9990e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 6.9982e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.9973e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.9962e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.9951e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 6.9938e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.9924e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.9908e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 6.9892e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.9877e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.9860e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 6.9844e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.9836e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.9827e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.9816e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 6.9803e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.9789e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.9775e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 6.9758e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.9739e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.9721e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.9704e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 6.9685e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 6.7488e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.3851 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 225/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 6.1022e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.0764e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.1203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.0919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 1.0560e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0306e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 1.0044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 9.7771e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.5252e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.3274e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 9.1451e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.9977e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 8.9035e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 8.8128e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 8.7228e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.6388e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.5640e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 8.4951e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.4259e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.3618e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.2982e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 8.2375e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 8.1791e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 8.1238e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 8.0724e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 8.0228e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 7.9747e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - 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7.6274e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.5930e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.5596e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.5273e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 7.4968e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.4665e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.4387e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 7.4115e-08 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 6.6101e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.6017e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.5935e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.5855e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 6.5775e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.5698e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.5624e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 6.5553e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.5482e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.5412e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.5342e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 6.5273e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.5204e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.5134e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 6.5065e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.4997e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.4930e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 6.4863e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.4798e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.4734e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.4672e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 6.4609e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.4547e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.4486e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 6.4425e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.4364e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.4304e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.4246e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 6.4188e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 5.7346e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.3878 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 226/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 1.0000 - loss: 5.6718e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 6.7747e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 1.0000 - loss: 6.8573e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 6.7183e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 6.5218e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 6.3611e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 6.2209e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 6.1126e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 6.0041e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 5.9307e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 5.8786e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 5.8328e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 5.7934e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 5.7611e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 5.7339e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 5.7035e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 5.6724e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 5.6527e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 5.6331e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 5.6111e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 5.5883e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 5.5663e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 5.5474e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 5.5297e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 5.5135e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 5.4997e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 5.4882e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 5.4775e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 5.4671e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 5.4577e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 5.4511e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.4440e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.4364e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.4285e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 5.4207e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.4134e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.4082e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 5.4037e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.3999e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.3955e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 5.3907e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 5.3861e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 5.3822e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 5.3772e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 5.3717e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 5.3666e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 5.3622e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 5.3575e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.3533e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.3492e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.3453e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.3412e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 5.3371e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 5.3327e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 5.3286e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.3247e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.3204e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.3161e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 5.3124e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 5.3085e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 5.3048e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 5.3011e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 5.2975e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 5.2938e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 5.2900e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.2873e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.2851e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.2831e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.2810e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.2788e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.2768e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.2761e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.2753e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.2746e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.2737e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.2725e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.2712e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.2698e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.2683e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.2668e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.2652e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.2639e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.2626e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.2614e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.2601e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.2593e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.2594e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.2592e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.2590e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.2588e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.2584e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.2581e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.2578e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.2574e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.2570e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 5.2566e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.2562e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.2558e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 5.2556e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.2551e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.2546e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.2551e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 5.2556e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.2559e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.2560e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 5.2560e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.2560e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.2561e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 5.2562e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.2562e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.2562e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.2561e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.2559e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.2556e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.2554e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.2550e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.2544e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.2539e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.2534e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.2529e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 5.1882e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.3901 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 227/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 5.6143e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 5.3392e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.2429e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 6.3690e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 6.3220e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 6.3022e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 6.2431e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.1527e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.0527e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.9625e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.8893e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.8149e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.7525e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.7215e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.6899e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.6563e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.6264e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.6018e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.5761e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.5506e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.5222e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.4986e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.4790e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.4596e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.4485e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.4384e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.4281e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.4173e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.4058e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.3954e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.3851e-08 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 5.0477e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 5.0440e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 5.0407e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 5.0374e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 5.0341e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 5.0311e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 5.0282e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 5.0254e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 5.0225e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.0197e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.0170e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.0142e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 5.0113e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.0085e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.0058e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.0030e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 5.0002e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.9975e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.9948e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.9920e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.9894e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.9866e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.9839e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.9815e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.9790e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.9766e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.9749e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.9731e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.9713e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.9696e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.9679e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.9660e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.9641e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.9623e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.9609e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.9595e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.9579e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.9563e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.9547e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.9531e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 4.7675e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.3925 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 228/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 294ms/step - accuracy: 1.0000 - loss: 4.9438e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 4.7817e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 4.9059e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 4.8837e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 4.8370e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 4.7983e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 4.7510e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 4.7077e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 4.6803e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 4.6602e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 4.6454e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.6274e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.6471e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.6597e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.6706e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.6868e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.7064e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.7185e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.7291e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.7388e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.7456e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.7519e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.7607e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.7673e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.7746e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.7819e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.7882e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.7971e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.8038e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.8096e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 4.8205e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 4.8288e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.8345e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.8388e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 4.8423e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.8444e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.8460e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.8471e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 4.8490e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.8501e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.8506e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 4.8517e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.8525e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.8529e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 4.8523e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.8516e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.8515e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.8519e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 4.8530e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.8537e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.8543e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 4.8542e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.8539e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.8538e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.8532e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 4.8522e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.8508e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.8494e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 4.8481e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.8465e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.8450e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 4.8432e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.8415e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.8559e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.8700e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 4.8834e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.8961e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.9092e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 4.9215e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.9330e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.9441e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 4.9550e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.9653e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.9752e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.9846e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 4.9933e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.0014e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.0090e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 5.0164e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.0232e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.0296e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.0359e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 5.0419e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.0475e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.0528e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 5.0579e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.0673e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.0761e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 5.0845e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.0925e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.1033e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.1145e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 5.1251e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.1352e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.1451e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 5.1546e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 5.1639e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 5.1730e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 5.1816e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.1900e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.1980e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.2066e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 5.2149e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.2229e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.2314e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 5.2397e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.2479e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.2556e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 5.2631e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.2704e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 5.2775e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.2843e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 5.2907e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.2969e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.3031e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.3091e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.3148e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.3203e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.3256e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.3306e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 5.9271e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3923 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 229/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 4.4977e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 4.5657e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 4.6361e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 4.5594e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 4.4845e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 4.4133e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 4.3704e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 4.3689e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 4.3493e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 4.3330e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 4.3289e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 4.3729e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 4.4107e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 4.4448e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.4824e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.5122e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.5346e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 4.5525e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 4.5694e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 4.5838e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 4.5942e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 4.6036e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 4.6113e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 4.6704e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 4.7231e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 4.7701e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 4.8109e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 4.8454e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 4.8744e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 4.8992e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 4.9205e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 4.9389e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 4.9534e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 4.9663e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 4.9781e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 4.9875e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 4.9965e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 5.0044e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 5.0122e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 5.0184e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 5.0235e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 5.0274e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 5.0305e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 5.0327e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 5.0340e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 5.0350e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 5.0357e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 1.0000 - loss: 5.0357e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.0352e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.0344e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.0333e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 5.0315e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.0294e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.0273e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 5.0358e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.0432e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.0496e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.0554e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 5.0614e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.0667e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.0716e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 5.0759e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.0798e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.0834e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 5.0872e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.0905e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 5.0937e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.0963e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 5.0983e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.1002e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.1020e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 5.1033e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.1044e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.1053e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.1061e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 5.1065e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.1068e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.1069e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 5.1068e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.1073e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.1075e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 5.1077e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.1077e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.1082e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.1087e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 5.1090e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.1094e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.1095e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.1094e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.1093e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.1101e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 5.1106e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.1109e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.1112e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.1113e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.1129e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 5.1146e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 5.1163e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 5.1177e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.1190e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.1202e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.1212e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 5.1221e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.1228e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.1232e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.1235e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.1238e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.1241e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 5.1244e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.1245e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.1246e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.1246e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 5.1245e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1242e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1239e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 5.1235e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1229e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1224e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1219e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 5.1213e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 5.0544e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9772 - val_loss: 0.3949 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4992 Epoch 230/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 7.9753e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 7.0502e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.5127e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 6.1203e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.7912e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.6754e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.5713e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.2348e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.6485e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.9474e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.1779e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 7.3452e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.4649e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.5412e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 7.5862e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.6093e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.6126e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.6043e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.5891e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.5669e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.5401e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.5318e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.5217e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.5050e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.4857e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.4635e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.4402e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.4138e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.3853e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.3551e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.3292e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.3020e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.2728e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.2427e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.2125e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 7.1819e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.1526e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.1238e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 7.0979e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 7.0717e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 7.0452e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 7.0184e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9923e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9686e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9443e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.9197e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.8957e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.8716e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.8476e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 6.8238e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 6.8002e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 6.7764e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 6.7525e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 6.7298e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 6.8178e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 6.8998e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 6.9768e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.0490e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 7.1168e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.1807e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.2410e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 7.2980e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.3522e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.4030e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.4514e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 7.4988e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.5776e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.6526e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 7.7237e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.7919e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.8718e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 7.9484e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.0226e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 8.0940e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.1623e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.2410e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.3185e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.3933e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.7699e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.1322e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.4848e-08 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.0877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.7867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.4640e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.5168e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 4.5790e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 5.9155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.9551e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 1.0352e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.3811e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 1.9625e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.6118e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.5470e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 5.0365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.0378e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 9.3336e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.2140e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.5341e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 1.9052e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.3246e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.7961e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.3070e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.8657e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 4.4629e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.1069e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 5.8182e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 6.5910e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.3991e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.2618e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 9.1676e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.0091e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.1025e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 1.1978e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.2943e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.3914e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 1.4890e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9999 - loss: 1.5871e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9999 - loss: 1.6867e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9999 - loss: 1.7865e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9999 - loss: 1.8869e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9995 - loss: 0.0014 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 - val_accuracy: 0.9749 - val_loss: 0.2889 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4979 Epoch 231/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9981 - loss: 0.0050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4985  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9983 - loss: 0.0046 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4986  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9984 - loss: 0.0044 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9985 - loss: 0.0042 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4987  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9986 - loss: 0.0040 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9986 - loss: 0.0039 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9986 - loss: 0.0038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4988  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.9987 - loss: 0.0037 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9987 - loss: 0.0036 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9988 - loss: 0.0035 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4989  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9988 - loss: 0.0034 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9988 - loss: 0.0033 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9989 - loss: 0.0032 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4990  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9989 - loss: 0.0031 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9989 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9990 - loss: 0.0030 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9990 - loss: 0.0029 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9990 - loss: 0.0028 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4991  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9990 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9990 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9991 - loss: 0.0027 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9991 - loss: 0.0026 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9991 - loss: 0.0025 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9991 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9991 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4992  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9991 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9992 - loss: 0.0024 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9992 - loss: 0.0023 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9992 - loss: 0.0022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9992 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4993  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9993 - loss: 0.0021 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9993 - loss: 0.0020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9993 - loss: 0.0019 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9994 - loss: 0.0018 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4994  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9994 - loss: 0.0017 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9994 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9995 - loss: 0.0016 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9995 - loss: 0.0015 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4995 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9997 - loss: 8.0575e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4997 - val_accuracy: 0.9764 - val_loss: 0.3057 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 232/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9999 - loss: 1.7058e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9999 - loss: 2.0863e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9999 - loss: 2.2460e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9999 - loss: 2.4618e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9999 - loss: 2.6857e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9999 - loss: 2.8011e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9999 - loss: 2.8394e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9999 - loss: 2.8367e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9999 - loss: 2.8119e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9999 - loss: 2.7862e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9999 - loss: 2.7700e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9999 - loss: 2.7532e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9999 - loss: 2.7398e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9999 - loss: 2.7236e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9999 - loss: 2.7034e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9999 - loss: 2.6776e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9999 - loss: 2.6492e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9999 - loss: 2.6198e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9999 - loss: 2.5896e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9999 - loss: 2.5591e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9999 - loss: 2.5280e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9999 - loss: 2.4986e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9999 - loss: 2.4692e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9999 - loss: 2.4400e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9999 - loss: 2.4113e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9999 - loss: 2.3828e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9999 - loss: 2.3546e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9999 - loss: 2.3266e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9999 - loss: 2.2988e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9999 - loss: 2.2718e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9999 - loss: 2.2454e-04 - mean_absolute_error: 0.5000 - 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mean_squared_error: 0.4999  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9999 - loss: 2.0538e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9999 - loss: 2.0321e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9999 - loss: 2.0109e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9999 - loss: 1.9902e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9999 - loss: 1.9698e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9999 - loss: 1.9499e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9999 - loss: 1.9303e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9999 - loss: 1.9111e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9999 - loss: 1.8924e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9999 - loss: 1.8740e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9999 - loss: 1.8560e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9999 - loss: 1.8384e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9999 - loss: 1.8212e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9999 - loss: 1.8042e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9999 - loss: 1.7876e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9999 - loss: 1.7714e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9999 - loss: 1.7554e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9999 - loss: 1.7398e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9999 - loss: 1.7244e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9999 - loss: 1.7094e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9999 - loss: 1.6946e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9999 - loss: 1.6802e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9999 - loss: 1.6661e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.6523e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.6387e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.6253e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.6122e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.5993e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.5867e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.5742e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.5620e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.5500e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.5382e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.5266e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4999  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.5152e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.5040e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.4930e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.4821e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.4715e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.4610e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.4506e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.4405e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.4305e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.4206e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.4110e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.4014e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3920e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.3828e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3737e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3647e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.3559e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3472e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3386e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3302e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.3218e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3136e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.3055e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2975e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2897e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2819e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2742e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2667e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2592e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2519e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2447e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2375e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2304e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2235e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2166e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2098e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2031e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1965e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1900e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1835e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.1771e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1708e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1646e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.1585e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1524e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1464e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1405e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.1346e-04 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 4.3832e-05 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9769 - val_loss: 0.3107 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4988 Epoch 233/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 3.4457e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 3.4830e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.5019e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 3.4611e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.4084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.3656e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 3.3357e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.3104e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.2769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.2480e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.2276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.2050e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.1898e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.1798e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.1710e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.1590e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.1458e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.1339e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.1221e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.1098e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.0966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.0847e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.0746e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.0645e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.0558e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.0488e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.0429e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.0365e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.0294e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.0228e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.0162e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.0095e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.0022e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.9957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.9895e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.9831e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.9773e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.9719e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.9667e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.9617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.9565e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.9513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.9462e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.9410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.9354e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.9300e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.9249e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.9196e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.9146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.9097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.9052e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.9005e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.8957e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.8911e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.8866e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.8819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.8770e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.8723e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 2.8680e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.8637e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.8595e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 2.8555e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.8516e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.8475e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 2.8435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.8395e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.8355e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.8315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 2.8274e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.8233e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.8193e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 2.8154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.8116e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.8079e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.8044e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 2.8008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.7971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.7935e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 2.7899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.7863e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.7826e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.7789e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.7754e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.7718e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.7684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.7650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.7617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.7583e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.7549e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.7515e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.7482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.7449e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.7415e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.7381e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.7348e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.7315e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.7282e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.7250e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.7219e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.7186e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.7154e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.7122e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.7090e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.7058e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.7026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.6994e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.6962e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.6931e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.6901e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.6870e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.6840e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.6809e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.6778e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.6748e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 2.6718e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 2.6689e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.6660e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.6631e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.6602e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 2.6572e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 2.3111e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3188 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 234/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 1.0000 - loss: 1.9276e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 2.0067e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.0543e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 2.0146e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 1.9769e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.9502e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 1.9421e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 1.9247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.9084e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.8947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 1.8847e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.8733e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.8681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 1.8644e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.8617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.8578e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 1.0000 - loss: 1.8529e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.8478e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 1.0000 - loss: 1.8435e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.8383e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 1.8321e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.8266e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.8247e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 1.8220e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.8203e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.8190e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.8178e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 1.8161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.8141e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.8120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 1.8102e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.8078e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.8049e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 1.8021e-06 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.7278e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.7265e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 1.7252e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.7240e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.7227e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 1.7214e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.7201e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.7188e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 1.7175e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.7161e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.7147e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.7134e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 1.7120e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.7107e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.7094e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 1.7081e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.7068e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.7055e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.7042e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 1.7029e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.7016e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.7003e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 1.6989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.6976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.6963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 1.0000 - loss: 1.6950e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.6938e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.6925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.6912e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 1.0000 - loss: 1.6899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.6886e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.6873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 1.6860e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.6846e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.6832e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.6819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 1.6805e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 1.0000 - loss: 1.5183e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3252 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4989 Epoch 235/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.6819e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 1.0000 - loss: 1.6366e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 33s 291ms/step - accuracy: 1.0000 - loss: 1.6115e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 1.5653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 1.0000 - loss: 1.5259e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 1.4965e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.4790e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.4618e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.4442e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 1.4292e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 1.4170e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.4049e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.3966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.3899e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 1.3842e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.3785e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.3725e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 1.3677e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.3665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.3647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 1.3622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 1.3594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 1.3570e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.3546e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 1.3528e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.3513e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.3500e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 1.3482e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.3460e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.3442e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.3424e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 1.3410e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.3392e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.3374e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 1.3358e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.3341e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.3327e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 1.3314e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.3302e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.3287e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.3272e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 1.3258e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.3244e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.3231e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 1.3215e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.3201e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.3187e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 1.3173e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.3160e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.3148e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.3138e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 1.3126e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.3113e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.3101e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 1.3089e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3076e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3062e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3048e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 1.3035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.3021e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.3008e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 1.2996e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.2984e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.2972e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 1.2959e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.2947e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.2935e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.2922e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 1.2909e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.2897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.2885e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 1.2873e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.2861e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.2851e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.2840e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 1.2829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.2817e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.2806e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 1.2795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.2783e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.2772e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 1.2761e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2750e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 1.2739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2728e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.2719e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2705e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.2698e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2690e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2687e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.2684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2681e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.2674e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2671e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2667e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.2664e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2660e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2657e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2653e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.2650e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2647e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2643e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.2639e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2635e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2632e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.2628e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2624e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2620e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2616e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.2612e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.2599e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2594e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2589e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.2580e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.1987e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3292 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 236/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.2692e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.2164e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1867e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1461e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 1.1251e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1112e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1097e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1061e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 1.1007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 1.0925e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.0900e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.0882e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.0871e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 1.0850e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0861e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 1.0884e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0917e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 1.0934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0953e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0963e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 1.0976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.0989e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1006e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1018e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 1.1028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1036e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1041e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 1.1042e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1039e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 1.1030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 1.1030e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.1031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.1033e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 1.1035e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.1034e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.1031e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 1.1028e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.1025e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.1021e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 1.1014e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.1007e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.1002e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.0995e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 1.0988e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.0982e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.0976e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 1.0971e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.0966e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.0960e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.0954e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 1.0949e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.0941e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.0934e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 1.0927e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.0919e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.0912e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 1.0904e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.0897e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.0891e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.0883e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 1.0876e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.0869e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.0861e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 1.0852e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.0844e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.0836e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 1.0829e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.0822e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.0815e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.0809e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 1.0802e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.0795e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.0788e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 1.0781e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0774e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0767e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 1.0759e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0752e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0744e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0739e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 1.0735e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0731e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0726e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 1.0721e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0716e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0711e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0706e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 1.0700e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0694e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0689e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 1.0684e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0678e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0674e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 1.0670e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0665e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0661e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0656e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 1.0651e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0646e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0641e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 1.0636e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0632e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0627e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 1.0622e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0617e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0613e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0608e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 1.0603e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.0598e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.0593e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 1.0588e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.0584e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.0579e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.0575e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 1.0570e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 1.0026e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3326 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 237/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 1.3468e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.2110e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.1411e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.0776e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.0333e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 1.0046e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 1.0000 - loss: 9.8634e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 9.6904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 9.5145e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 9.3690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 1.0000 - loss: 9.2673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 1.0000 - loss: 9.1714e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 9.1094e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 9.0597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 9.0221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.9762e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.9306e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 1.0000 - loss: 8.8900e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.8564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.8229e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 1.0000 - loss: 8.8006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 8.7815e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.7706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 8.7585e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.7492e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.7422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 8.7344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 8.7244e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 8.7136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 8.7019e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 8.6919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.6795e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.6664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 8.6550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 8.6447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.6336e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.6237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 1.0000 - loss: 8.6149e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.6068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.5979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 1.0000 - loss: 8.5886e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 1.0000 - loss: 8.5792e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.6627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 8.6763e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.6893e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.7016e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.7131e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 8.7236e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.7332e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.7422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 8.7511e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.7594e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.7667e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 8.7736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.7801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 8.7859e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 8.8232e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.8263e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.8290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.8317e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 8.8341e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.8363e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.8386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 8.8406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.8422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.8434e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.8445e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 8.8456e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.8466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.8471e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 8.8477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.8482e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.8483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 8.8485e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.8488e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.8490e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.8489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 8.8486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.8483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.8478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 8.8471e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.8461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.8450e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.8439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 8.8426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 8.6822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3364 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 238/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 1.0123e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 1.0218e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 1.0042e-06 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.6767e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.3426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.1914e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 1.0000 - loss: 9.0677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 8.9350e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 8.7920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 1.0000 - loss: 8.6795e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 8.5898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 8.5088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 8.4413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 1.0000 - loss: 8.3872e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 8.3457e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 8.2979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 1.0000 - loss: 8.2514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 8.2062e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 8.1649e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 8.1241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 1.0000 - loss: 8.0828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 1.0000 - loss: 8.0444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 1.0000 - loss: 8.0107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 1.0000 - loss: 7.9803e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 7.9525e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 1.0000 - loss: 7.9284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 1.0000 - loss: 7.9057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 1.0000 - loss: 7.8821e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 7.8579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 7.8365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 1.0000 - loss: 7.8157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 7.7941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 7.7713e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 1.0000 - loss: 7.7486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 7.7281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 7.7080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 7.6893e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 7.6721e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 7.6558e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 7.6386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 7.6224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 7.6065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 7.5917e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 7.5773e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 7.7249e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 7.8621e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 7.9913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 8.1111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.2241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 8.3298e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 8.4295e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 8.5224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 8.6092e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 8.6915e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 8.7689e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 8.8409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 8.9083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 8.9716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 9.0314e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.0871e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.1397e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 9.1897e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.2369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.2807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 9.3221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.3611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.3980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.4324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 1.0000 - loss: 9.4647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 9.4951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 9.5239e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 1.0000 - loss: 9.5510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.5768e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.6013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.6245e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 9.6459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.6659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.6849e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 9.7027e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.7193e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.7346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 9.7489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.7627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.7755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.7877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 9.7993e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 9.8101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 9.8198e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 9.8287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.8371e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.8449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.8522e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 9.8586e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.8646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.8704e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 9.8755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.8801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.8844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 9.8885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.8946e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.9002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.9055e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 9.9103e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.9146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.9186e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 9.9221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.9253e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.9281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 9.9307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.9329e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.9351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.9378e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 9.9401e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.9422e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.9440e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 9.9454e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.9465e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.9473e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.9480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 9.9484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 9.9979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3411 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 239/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 8.8237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 8.8282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.9678e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.7514e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 8.6222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 8.5066e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 8.4170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 8.3170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.2037e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.1181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 8.0552e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 7.9879e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 7.9351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 7.8928e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 7.8619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 7.8286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.7990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.7692e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 7.7418e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.7205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.6957e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 7.6736e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.6545e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.6345e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 7.6177e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.6028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.5901e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.5765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 7.5631e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.5498e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 7.5368e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.1261e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 7.1214e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.1171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.1128e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.1086e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 7.1045e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.1005e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.0963e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 7.0920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.0876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.0832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 7.0787e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.0741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.0694e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.0647e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 7.0601e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.0555e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.0511e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 7.0468e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.0424e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.0379e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.0334e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 7.0289e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.0245e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.0200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 7.0156e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.0113e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.0069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 7.0026e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 6.9984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 6.9942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 6.9899e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 6.9855e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 6.9812e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 6.9769e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 6.9725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.9706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.9688e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.9670e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 6.9652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 6.7441e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3422 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 240/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 7.6633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 7.4576e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 7.5513e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 7.3864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 7.1875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 7.0361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.9276e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 6.8157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 6.7120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.6538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.6457e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 6.6284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.6200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.6144e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.6135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 6.6017e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.5871e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.5709e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 6.5581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.5420e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.5225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 6.5039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.4868e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.4684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.4526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 6.4391e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.4266e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.4129e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 6.3995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.3860e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.3737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 6.3623e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.3494e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.3359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.3239e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 6.3112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.2990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.2878e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 6.2771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.2658e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.2547e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 6.2437e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.2329e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.2224e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.2117e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 6.2010e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.1913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.1812e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 6.1719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.1641e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.1572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 6.1651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.1720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.1781e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.1838e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 6.1898e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.1949e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.1995e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 6.2035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.2069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.2104e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 6.2137e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.2167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.2191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.2211e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 6.2227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.2240e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.2250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 6.2254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.2254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.2255e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.2253e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 6.2252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.2255e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.2257e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 6.2255e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.2250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.2243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 6.2241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.2236e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.2229e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.2223e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 6.2216e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.2207e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.2199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 6.2191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.2181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.2169e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 6.2157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.2146e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.2135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.2120e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 6.2102e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.2084e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.2067e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 6.2048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.2030e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.2013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 6.1997e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.1978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.1959e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.1941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 6.1925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.1906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.1885e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 6.1864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.1843e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.1821e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 6.1799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.1778e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.1757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.1734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 6.1710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.1686e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.1662e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 6.1637e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.1611e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.1583e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.1557e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 6.1529e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 5.8221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3450 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 241/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.6205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 1.0000 - loss: 5.9340e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 6.0825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.9726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 5.8765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.7882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.7127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.6629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 5.6018e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.5590e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.5313e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 5.4971e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.4740e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.4591e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 5.4555e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.4454e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.4324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.4217e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 5.4100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.3950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.3784e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 5.3629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.3500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.3354e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.3236e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 5.3129e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.3031e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.2917e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 5.2810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.2700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.2597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 5.2486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.2369e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.2254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.2148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 5.2040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.1944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.1854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 5.1771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.1684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.1595e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 5.1539e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.1485e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.1424e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.1359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 5.1292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 5.1233e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 5.1171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 5.1110e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 5.1054e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 5.1006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 5.0952e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 5.0900e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 5.0846e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 5.0795e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 5.0463e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 5.0428e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 5.0392e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 5.0359e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 5.0326e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 5.0291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 5.0253e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 5.0215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 5.0179e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 5.0143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 5.0113e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 5.0083e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 5.0061e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 5.0037e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.9825e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.9799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 4.9775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.9752e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.9727e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 4.9701e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.9677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.9652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.9627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 4.9599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.9572e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.9546e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 4.9521e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.9497e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.9473e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 4.9449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.9425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.9431e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.9436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 4.9442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.9446e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.9449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 4.9455e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.9461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.9465e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 4.9469e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.9474e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.9478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.9483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 4.9487e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.9491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.9495e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 4.9497e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.9499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.9499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.9498e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 4.9497e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 4.9352e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3470 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 Epoch 242/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 4.7432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 5.0256e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 5.0872e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.9804e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 4.8964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 4.8358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.7730e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.7012e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.6291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.5726e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.5351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.4991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.4741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.4559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.4445e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 4.4272e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.4112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3951e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 4.3828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3574e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 4.3510e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.3459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.3398e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.3364e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 4.3344e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.3331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.3311e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 4.3284e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.3254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.3220e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 4.3179e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.3126e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.3085e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.3049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 4.3007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.2967e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.2933e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 4.2908e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.2876e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.2841e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 4.2807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.2772e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.2734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.2691e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 4.2646e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.2608e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.2568e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 4.2534e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.2503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.2476e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 4.2442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 4.2323e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2292e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2262e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 4.2235e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 4.2160e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2104e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 4.2084e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.2065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.2044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 4.2022e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.2001e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.1984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 4.1966e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.1950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.1935e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.1920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 4.1905e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.1889e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.1872e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 4.1857e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.1840e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.1823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 4.1807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.1792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.1776e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.1763e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 4.1750e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.1738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.1725e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 4.1710e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.1694e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.1679e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.1662e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 4.1645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.1629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.1613e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 4.1596e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.1580e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.1564e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 4.1549e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.1533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.1516e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.1500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 4.1483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.1466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.1448e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 4.1432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.1416e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.1399e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 4.1384e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.1368e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.1354e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.1339e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 4.1324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.1310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.1296e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 4.1282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.1267e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.1252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.1237e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 4.1222e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 3.9377e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3498 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 243/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 6.2863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 5.8071e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 5.4650e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 1.0000 - loss: 5.1532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 4.9346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 4.7860e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 4.6968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 4.6174e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 4.5351e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 4.4644e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 1.0000 - loss: 4.4046e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 4.3481e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 4.3037e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 1.0000 - loss: 4.2656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.2656e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.2594e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.2501e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.2459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.2408e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.2327e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.2219e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.2104e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.2006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.1892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.1806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.1747e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.1695e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 4.1628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.1561e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.1491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.1423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 4.1380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.1331e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.1278e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 4.1228e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.1179e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.1137e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 4.1099e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.1061e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.1014e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.0964e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 1.0000 - loss: 4.0911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.0861e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.0816e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 4.0764e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.0711e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.0663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 1.0000 - loss: 4.0614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.0567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 4.0524e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.0481e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 4.0436e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.0388e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.0341e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 4.0297e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.0250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 4.0200e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.0151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 4.0107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 4.0063e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 4.0020e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 1.0000 - loss: 3.9978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.9938e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.9895e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 1.0000 - loss: 3.9852e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.9538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.9504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.9472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 1.0000 - loss: 3.9439e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.9406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.9373e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 1.0000 - loss: 3.9343e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.9312e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.9279e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 3.9248e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.9220e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.9191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.9164e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 3.9138e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.9112e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.9086e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 3.9059e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.9032e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.9011e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 3.8988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.8965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.8941e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.8918e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 3.8895e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.8872e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.8851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 3.8830e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.8809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.8787e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.8765e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 3.8745e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.8724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.8702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 3.8681e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.8660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.8639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 3.8619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.8599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.8579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.8561e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 3.8542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.8523e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.8504e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 3.8484e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.8464e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.8444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.8423e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 3.8403e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 3.5960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3529 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 244/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 1.0000 - loss: 3.6614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 1.0000 - loss: 3.8309e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.8735e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 1.0000 - loss: 3.8493e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.7882e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.7381e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 1.0000 - loss: 3.7004e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 1.0000 - loss: 3.6532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.6029e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.5654e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.5459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 3.5307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.5199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.5123e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.5070e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5124e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.5185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.5181e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.5148e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 3.5105e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.5081e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.5040e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 3.5048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.5059e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.5076e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.5069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.5057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 1.0000 - loss: 3.5049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.5037e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.5041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.5041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.5044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 1.0000 - loss: 3.5049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.5047e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.5049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 1.0000 - loss: 3.5051e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.5056e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.5051e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.5048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.5042e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.5037e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 1.0000 - loss: 3.5028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.5013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.5000e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.4990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.4979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.4974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.4969e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.4965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 1.0000 - loss: 3.4957e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 1.0000 - loss: 3.4948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.4940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.4932e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.4920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 1.0000 - loss: 3.4905e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.4891e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.4878e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.4863e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.4848e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.4836e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.4822e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.4807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.4791e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.4773e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.4755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.4737e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.4716e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.4696e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.4677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.4658e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.4638e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.4619e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.4602e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.4584e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.4567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.4550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.4532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.4516e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.4498e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.4480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.4461e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.4443e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.4426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 3.4410e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.4396e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.4381e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 3.4366e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.4350e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.4335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.4318e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 3.4307e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.4294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.4282e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 3.4269e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.4257e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.4244e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 3.4236e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.4229e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.4223e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.4217e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 3.4209e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.4201e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.4192e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 3.4183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.4173e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.4169e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 3.4166e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.4162e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.4159e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.4157e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 3.4155e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.4153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.4152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 3.4150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.4147e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.4143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.4140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 3.4137e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 3.3720e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3549 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 245/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.8648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.5494e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.6919e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.6979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.6575e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.9774e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.1570e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.2412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 4.2708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.2806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 4.2850e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 4.2756e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.2621e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 4.2444e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 4.2251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.2023e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.1784e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 4.1557e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.1342e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.1111e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.0869e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 4.0643e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.0443e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.0235e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 4.0036e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 3.9851e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 1.0000 - loss: 3.9678e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 3.9500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.9324e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.9160e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.9006e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 3.8847e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.8691e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.8548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 3.8413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.8275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.8143e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.8018e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 3.7903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.7787e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.7674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 3.7565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.7458e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.7361e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 3.7265e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.7171e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.7080e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.6989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 3.6903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.6824e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.6749e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 3.6767e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.6780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.6791e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.6801e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 3.6806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.6807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.6808e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 3.6807e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.6802e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.6798e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 3.6792e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.6788e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.6780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.6770e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 3.6758e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.6746e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.6731e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 3.6715e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.6697e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.6680e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 3.6660e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.6642e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.6628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.6615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 3.6599e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.6582e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.6565e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 3.6550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.6533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 3.6516e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.6499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 3.6483e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.6466e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.6449e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 3.6432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.6415e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.6396e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 3.6377e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.6358e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.6339e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.6318e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 3.6297e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.6275e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.6254e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 3.6231e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.6209e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.6189e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 3.6170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.6150e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.6130e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.6110e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 3.6089e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.6069e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.6048e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 3.6028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.6007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.5986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 3.5965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5945e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5925e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 3.5883e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.5862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.5841e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 3.5820e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.5799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.5777e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.5755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 3.5734e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 3.3141e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3559 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 246/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.6177e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.5372e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.4503e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.3546e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 1.0000 - loss: 3.2717e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 3.2127e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 3.1674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 3.1406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.1064e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.0775e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.0618e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 296ms/step - accuracy: 1.0000 - loss: 3.0438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.0376e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.0337e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 1.0000 - loss: 3.0287e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.0202e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.0130e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 1.0000 - loss: 3.0057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.9986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.9911e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.9828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 1.0000 - loss: 2.9750e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.9684e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.9614e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 1.0000 - loss: 2.9568e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.9532e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.9497e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.9454e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 1.0000 - loss: 2.9412e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.9380e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.9349e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 1.0000 - loss: 2.9318e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.9286e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.9252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 1.0000 - loss: 2.9221e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.9188e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.9161e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.9136e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 1.0000 - loss: 2.9114e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.9090e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.9063e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 1.0000 - loss: 2.9035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.9007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.8980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.8953e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 1.0000 - loss: 2.8927e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.8903e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.8880e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 1.0000 - loss: 2.8862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.8845e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.8828e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.8810e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.8789e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.8773e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.8757e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.8741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.8723e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.8733e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.8750e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.8764e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.8781e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.8797e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.8813e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.8827e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.8839e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.8852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.8864e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.8877e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.8892e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.8905e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.8918e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.8929e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.8940e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.8950e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 1.0000 - loss: 2.8960e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.8968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.8975e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.8980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 1.0000 - loss: 2.8985e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.8988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.8991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 1.0000 - loss: 2.8991e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.8990e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.8989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.8989e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.8988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.8986e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.8984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.8982e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.8979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.8976e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.8974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.8977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.8979e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.8980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.8981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.8982e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.8982e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.8981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.8981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.8980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.8978e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.8977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.8977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.8976e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.8974e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.8972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.8970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.8968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.8965e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.8961e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.8958e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.8955e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.8586e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9770 - val_loss: 0.3574 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 247/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.0366e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.1694e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.1669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 3.0957e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.0296e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.9867e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.9530e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.9151e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.8759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.8426e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.8153e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.7913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.7750e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.7636e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.7562e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.7469e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.7371e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.7288e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.7215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.7137e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.7053e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.6977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.6906e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.6840e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.6786e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.6739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.6696e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.6645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.6593e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.6542e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.6499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.6457e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.6411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.6362e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.6321e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.6280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.6241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.6203e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.6170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.6135e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.6099e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.6066e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.6035e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.6003e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.5968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.5933e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.5904e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.5875e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.5848e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.5826e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.5809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 1.0000 - loss: 2.5790e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.5771e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.5754e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.5739e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 1.0000 - loss: 2.5724e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.5707e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.5690e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 1.0000 - loss: 2.5677e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.5663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.5651e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 1.0000 - loss: 2.5640e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.5629e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.5617e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.5604e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 1.0000 - loss: 2.5592e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.5580e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.5567e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 1.0000 - loss: 2.5553e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.5538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.5525e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.5512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5500e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5480e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.5470e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5460e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.5442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.5491e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.5537e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 1.0000 - loss: 2.5581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.5627e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.5670e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.5712e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 1.0000 - loss: 2.5752e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.5795e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.5834e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 1.0000 - loss: 2.5872e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.5909e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.5944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 1.0000 - loss: 2.5977e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.6009e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.6039e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.6068e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 1.0000 - loss: 2.6097e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.6124e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.6152e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 1.0000 - loss: 2.6179e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.6204e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.6227e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.6250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 1.0000 - loss: 2.6273e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.6294e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.6315e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 1.0000 - loss: 2.6335e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.6355e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.6373e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 1.0000 - loss: 2.6390e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.6408e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.6425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.6442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 1.0000 - loss: 2.6457e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.6472e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.6486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 1.0000 - loss: 2.6499e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.6512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.6525e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.6538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 1.0000 - loss: 2.6550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 1.0000 - loss: 2.7970e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3578 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 248/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 3.0598e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 1.0000 - loss: 3.0836e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 3.0404e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.9374e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.8738e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.8252e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.7817e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.7406e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.6988e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.6633e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.6393e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 1.0000 - loss: 2.6233e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.6109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.6018e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.5944e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5901e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5859e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5836e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.5809e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.5762e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.5702e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.5821e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.5930e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.6014e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.6214e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.6389e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.6548e-07 - 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mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.8316e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.8308e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 1.0000 - loss: 2.8300e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.8291e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.8281e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 1.0000 - loss: 2.8271e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.8261e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.8251e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.8243e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 1.0000 - loss: 2.8234e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.8225e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.8215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 1.0000 - loss: 2.8205e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.8195e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.8185e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 1.0000 - loss: 2.8175e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.8167e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.8158e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.8149e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 1.0000 - loss: 2.8140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.8130e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.8119e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 1.0000 - loss: 2.8109e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.8098e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.8088e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 1.0000 - loss: 2.8077e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.8065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.8055e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.8043e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 1.0000 - loss: 2.8031e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.8019e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.8007e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 1.0000 - loss: 2.7994e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.7981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.7968e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.7956e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 1.0000 - loss: 2.7942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 1.0000 - loss: 2.6373e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3615 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 249/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.9799e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 1.0000 - loss: 2.8880e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 1.0000 - loss: 2.8527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.7854e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.7049e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 1.0000 - loss: 2.6489e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.6020e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.5581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 1.0000 - loss: 2.5140e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.4797e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.4534e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 1.0000 - loss: 2.4295e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.4086e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.3938e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 1.0000 - loss: 2.3806e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 1.0000 - loss: 2.3658e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3525e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 1.0000 - loss: 2.3301e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.3191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.3078e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 1.0000 - loss: 2.2980e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.2913e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.2844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.2783e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 1.0000 - loss: 2.2728e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.2680e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.2628e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 1.0000 - loss: 2.2576e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.2530e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.2486e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 1.0000 - loss: 2.2442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.2394e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.2346e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.2305e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 1.0000 - loss: 2.2265e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.2231e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.2199e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 1.0000 - loss: 2.2170e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.2139e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.2107e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 1.0000 - loss: 2.2075e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.2044e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.2013e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.1981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 1.0000 - loss: 2.1948e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.1920e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.1894e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 1.0000 - loss: 2.1872e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.1852e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.1837e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 1.0000 - loss: 2.1823e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1808e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1794e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1780e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 1.0000 - loss: 2.1768e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.1755e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.1743e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 1.0000 - loss: 2.1731e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.1719e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.1708e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 1.0000 - loss: 2.1700e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.1692e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.1683e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.1676e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 1.0000 - loss: 2.1669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.1664e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.1658e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 1.0000 - loss: 2.1652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1645e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 1.0000 - loss: 2.1639e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 1.0000 - loss: 2.1632e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.1626e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.1621e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.1616e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 1.0000 - loss: 2.1609e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.1602e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.1595e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 1.0000 - loss: 2.1588e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.1581e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.1574e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 1.0000 - loss: 2.1566e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.1559e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.1551e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.1544e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 1.0000 - loss: 2.1538e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.1533e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.1527e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 1.0000 - loss: 2.1522e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.1517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.1512e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.1507e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 1.0000 - loss: 2.1502e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.1496e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.1492e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 1.0000 - loss: 2.1487e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.1482e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.1478e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 1.0000 - loss: 2.1473e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.1469e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.1463e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.1459e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 1.0000 - loss: 2.1455e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.1451e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.1447e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 1.0000 - loss: 2.1442e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.1438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.1433e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 1.0000 - loss: 2.1429e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.1425e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.1420e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.1416e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 1.0000 - loss: 2.1411e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.1407e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.1403e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 1.0000 - loss: 2.1399e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.1395e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.1390e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.1386e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 1.0000 - loss: 2.1381e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 1.0000 - loss: 2.0842e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3634 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4991 Epoch 250/250  1/120 ━━━━━━━━━━━━━━━━━━━━ 36s 304ms/step - accuracy: 1.0000 - loss: 2.0427e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 1.0000 - loss: 2.0586e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.1902e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.2101e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 1.0000 - loss: 2.1998e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 1.0000 - loss: 2.1832e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.1844e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.1862e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 1.0000 - loss: 2.1759e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.1663e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.1579e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 1.0000 - loss: 2.1469e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.1376e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.1299e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 1.0000 - loss: 2.1241e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.1172e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.1104e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 1.0000 - loss: 2.1034e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.0981e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.0992e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 1.0000 - loss: 2.0984e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.0983e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 1.0000 - loss: 2.0994e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.1405e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 1.0000 - loss: 2.1772e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.2100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.2399e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 1.0000 - loss: 2.2655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.2880e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.3079e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 1.0000 - loss: 2.3260e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.3419e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.3554e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.3673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 1.0000 - loss: 2.3779e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 2.3870e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 2.3959e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 1.0000 - loss: 2.4041e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.4118e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.4183e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.4240e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 1.0000 - loss: 2.4290e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.4336e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.4376e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 1.0000 - loss: 2.4409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.4438e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.4465e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 1.0000 - loss: 2.4493e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.4517e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.4546e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.4574e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 1.0000 - loss: 2.4597e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 2.4615e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 2.4630e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 1.0000 - loss: 2.4642e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.4652e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.4658e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 1.0000 - loss: 2.4661e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.4666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.4669e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.4671e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 1.0000 - loss: 2.4672e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.4674e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.4673e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 1.0000 - loss: 2.4670e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.4666e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.5197e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.5706e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 1.0000 - loss: 2.6191e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 2.6655e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 2.7100e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 1.0000 - loss: 2.7526e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.7934e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.8328e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 1.0000 - loss: 2.8705e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.9065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.9409e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 2.9741e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 1.0000 - loss: 3.0059e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.0365e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.0659e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 1.0000 - loss: 3.0942e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.1215e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.1477e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.1729e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 1.0000 - loss: 3.1972e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2207e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2432e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 1.0000 - loss: 3.2648e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.2856e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.3057e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 1.0000 - loss: 3.3250e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.3435e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.3613e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.3786e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 1.0000 - loss: 3.4105e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.4413e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.4712e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 1.0000 - loss: 3.5001e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.5280e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.5550e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.5811e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 1.0000 - loss: 3.6065e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.6310e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.6548e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 1.0000 - loss: 3.6778e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 3.7002e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 3.7219e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 1.0000 - loss: 3.7430e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.7635e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.7835e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.8028e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 1.0000 - loss: 3.8216e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 1.0000 - loss: 3.8398e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.8574e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 1.0000 - loss: 3.8746e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.8912e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.9073e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.9231e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 1.0000 - loss: 3.9385e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 1.0000 - loss: 5.7703e-07 - mean_absolute_error: 0.5000 - mean_squared_error: 0.5000 - val_accuracy: 0.9771 - val_loss: 0.3492 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4990 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 473ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 483ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 45ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 55ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 58ms/step 1/1 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