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 1/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 9:48 5s/step - accuracy: 0.3579 - loss: 1.0724 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3099  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.3782 - loss: 1.0507 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3091  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.3884 - loss: 1.0429 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3094  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.3956 - loss: 1.0257 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3076  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.4044 - loss: 1.0051 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3054  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 296ms/step - accuracy: 0.4160 - loss: 0.9838 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3033  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.4298 - loss: 0.9625 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3015  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.4452 - loss: 0.9415 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3000  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.4610 - loss: 0.9212 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2989  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.4765 - loss: 0.9020 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2981  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.4912 - loss: 0.8838 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2975  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.5055 - loss: 0.8665 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2972  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.5191 - loss: 0.8499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2971  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.5321 - loss: 0.8342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2972  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.5445 - loss: 0.8192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2973  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.5562 - loss: 0.8050 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2976  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.5673 - loss: 0.7916 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2980  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.5777 - loss: 0.7788 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2984  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.5877 - loss: 0.7666 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2989  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.5971 - loss: 0.7549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.2995  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.6061 - loss: 0.7438 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3001  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.6146 - loss: 0.7331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3007  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.6226 - loss: 0.7229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3014  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.6303 - loss: 0.7131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3021  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.6376 - loss: 0.7038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3029  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.6445 - loss: 0.6948 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3036  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.6511 - loss: 0.6861 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3044  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.6575 - loss: 0.6778 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3052  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.6635 - loss: 0.6697 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3060  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.6693 - loss: 0.6620 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3068  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.6749 - loss: 0.6545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3076  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.6802 - loss: 0.6473 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3084  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.6853 - loss: 0.6403 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3092  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.6903 - loss: 0.6335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3100  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.6950 - loss: 0.6270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3108  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.6995 - loss: 0.6207 - mean_absolute_error: 0.5000 - 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━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.7305 - loss: 0.5764 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3181  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.7338 - loss: 0.5715 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3189  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.7370 - loss: 0.5668 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3197  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.7401 - loss: 0.5621 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3204  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.7431 - loss: 0.5576 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3212  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.7460 - loss: 0.5532 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3220  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.7489 - loss: 0.5490 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3227  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - 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mean_squared_error: 0.3333  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.7852 - loss: 0.4921 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3339  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.7871 - loss: 0.4891 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3346  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.7888 - loss: 0.4862 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3352  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.7906 - loss: 0.4834 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3359  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.7923 - loss: 0.4806 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3365  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.7940 - loss: 0.4778 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3371  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.7956 - loss: 0.4751 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3377  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.7972 - loss: 0.4725 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3383  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.7988 - loss: 0.4699 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3389  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.8003 - loss: 0.4673 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3395  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.8018 - loss: 0.4648 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3401  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.8033 - loss: 0.4624 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3406  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.8047 - loss: 0.4600 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3412  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.8061 - loss: 0.4576 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3418  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - 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━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.8325 - loss: 0.4119 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3532 103/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.8334 - loss: 0.4102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3537 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.8343 - loss: 0.4086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3541 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.8352 - loss: 0.4070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3546 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.8361 - loss: 0.4054 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3550 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.8370 - loss: 0.4038 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3554 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.8378 - loss: 0.4022 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3558 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.8387 - loss: 0.4007 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3563 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.8395 - loss: 0.3991 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3567 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.8404 - loss: 0.3976 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3571 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.8412 - loss: 0.3961 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3575 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.8420 - loss: 0.3947 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3579 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.8428 - loss: 0.3932 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3583 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.8436 - loss: 0.3918 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3587 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.8443 - loss: 0.3904 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3591 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.8451 - loss: 0.3889 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3595 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.8458 - loss: 0.3876 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3599 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.8466 - loss: 0.3862 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3603 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.8473 - loss: 0.3848 - mean_absolute_error: 0.5000 - mean_squared_error: 0.3606 120/120 ━━━━━━━━━━━━━━━━━━━━ 40s 298ms/step - accuracy: 0.9343 - loss: 0.2233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4061 - val_accuracy: 0.9608 - val_loss: 0.1808 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4387 Epoch 2/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 0.9649 - loss: 0.1383 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4536  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9646 - loss: 0.1365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4545  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9652 - loss: 0.1339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4543  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 291ms/step - accuracy: 0.9662 - loss: 0.1307 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4542  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 291ms/step - accuracy: 0.9669 - loss: 0.1288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4539  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 291ms/step - accuracy: 0.9675 - loss: 0.1273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4536  7/120 ━━━━━━━━━━━━━━━━━━━━ 32s 291ms/step - accuracy: 0.9680 - loss: 0.1261 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4535  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 291ms/step - accuracy: 0.9684 - loss: 0.1249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4535  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9687 - loss: 0.1238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4536  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9689 - loss: 0.1231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4537  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9691 - loss: 0.1225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4538  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9692 - loss: 0.1220 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4538  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9693 - loss: 0.1217 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4539  14/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9693 - loss: 0.1214 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4539  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9693 - loss: 0.1212 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4540  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9694 - loss: 0.1208 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4540  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9695 - loss: 0.1205 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4541  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9695 - loss: 0.1202 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4542  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9696 - loss: 0.1199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4542  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9697 - loss: 0.1196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4543  21/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9697 - loss: 0.1193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4543  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9698 - loss: 0.1190 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4544  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9698 - loss: 0.1188 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4545  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9699 - loss: 0.1186 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4545  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 292ms/step - accuracy: 0.9699 - loss: 0.1184 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4546  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 292ms/step - accuracy: 0.9700 - loss: 0.1182 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4546  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 292ms/step - accuracy: 0.9700 - loss: 0.1180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4547  28/120 ━━━━━━━━━━━━━━━━━━━━ 26s 292ms/step - accuracy: 0.9700 - loss: 0.1178 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4548  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 292ms/step - accuracy: 0.9701 - loss: 0.1176 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4548  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 292ms/step - accuracy: 0.9701 - loss: 0.1174 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4549  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 292ms/step - accuracy: 0.9701 - loss: 0.1172 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4549  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9702 - loss: 0.1170 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4550  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9702 - loss: 0.1168 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4551  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9703 - loss: 0.1166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4551  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 0.9703 - loss: 0.1164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4552  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 0.9703 - loss: 0.1162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4553  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 0.9704 - loss: 0.1160 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4553  38/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 0.9704 - loss: 0.1159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4554  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 0.9704 - loss: 0.1157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4554  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 0.9704 - loss: 0.1156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4555  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 0.9705 - loss: 0.1154 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4555  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 0.9705 - loss: 0.1152 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4556  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 0.9705 - loss: 0.1151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4557  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 0.9705 - loss: 0.1149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4557  45/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9706 - loss: 0.1148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4558  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9706 - loss: 0.1146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4559  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9706 - loss: 0.1144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4559  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9707 - loss: 0.1143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4560  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9707 - loss: 0.1142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4560  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9707 - loss: 0.1140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4561  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9707 - loss: 0.1139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4562  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9707 - loss: 0.1138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4562  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9708 - loss: 0.1136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4563  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9708 - loss: 0.1135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4563  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9708 - loss: 0.1134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4564  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9708 - loss: 0.1132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4564  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9709 - loss: 0.1131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4565  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9709 - loss: 0.1130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4566  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9709 - loss: 0.1128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4566  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9709 - loss: 0.1127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4567  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9709 - loss: 0.1126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4567  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9709 - loss: 0.1125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4568  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 293ms/step - accuracy: 0.9710 - loss: 0.1123 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4568  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 293ms/step - accuracy: 0.9710 - loss: 0.1122 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4569  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 293ms/step - accuracy: 0.9710 - loss: 0.1121 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4569  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 293ms/step - accuracy: 0.9710 - loss: 0.1120 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4570  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 293ms/step - accuracy: 0.9710 - loss: 0.1119 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4570  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 293ms/step - accuracy: 0.9711 - loss: 0.1118 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4571  69/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9711 - loss: 0.1116 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4572  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9711 - loss: 0.1115 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4572  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9711 - loss: 0.1114 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4573  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9711 - loss: 0.1113 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4573  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9711 - loss: 0.1112 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4574  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9712 - loss: 0.1111 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4574  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9712 - loss: 0.1110 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4575  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9712 - loss: 0.1109 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4575  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9712 - loss: 0.1108 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4576  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9712 - loss: 0.1107 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4576  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9712 - loss: 0.1106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4577  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9713 - loss: 0.1104 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4577  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9713 - loss: 0.1103 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4578  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9713 - loss: 0.1102 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4578  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9713 - loss: 0.1101 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4579  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 294ms/step - accuracy: 0.9713 - loss: 0.1100 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4579  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9713 - loss: 0.1099 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4580  86/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9714 - loss: 0.1098 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4580   87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9714 - loss: 0.1097 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4580  88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9714 - loss: 0.1096 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4581  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9714 - loss: 0.1095 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4581  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9714 - loss: 0.1094 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4582  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9714 - loss: 0.1093 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4582  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9715 - loss: 0.1092 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4583  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9715 - loss: 0.1091 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4583  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9715 - loss: 0.1090 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4584  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9715 - loss: 0.1090 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4584  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9715 - loss: 0.1089 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4585  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 293ms/step - accuracy: 0.9715 - loss: 0.1088 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4585  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 293ms/step - accuracy: 0.9715 - loss: 0.1087 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4585  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 293ms/step - accuracy: 0.9716 - loss: 0.1086 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4586 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 293ms/step - accuracy: 0.9716 - loss: 0.1085 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4586 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 293ms/step - accuracy: 0.9716 - loss: 0.1084 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4587 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 293ms/step - accuracy: 0.9716 - loss: 0.1083 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4587 103/120 ━━━━━━━━━━━━━━━━━━━━ 4s 293ms/step - accuracy: 0.9716 - loss: 0.1082 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4588 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 293ms/step - accuracy: 0.9716 - loss: 0.1081 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4588 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 293ms/step - accuracy: 0.9716 - loss: 0.1080 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4589 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 293ms/step - accuracy: 0.9717 - loss: 0.1079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4589 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 293ms/step - accuracy: 0.9717 - loss: 0.1079 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4589 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 293ms/step - accuracy: 0.9717 - loss: 0.1078 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4590 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 293ms/step - accuracy: 0.9717 - loss: 0.1077 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4590 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 293ms/step - accuracy: 0.9717 - loss: 0.1076 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4591 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 293ms/step - accuracy: 0.9717 - loss: 0.1075 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4591 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 293ms/step - accuracy: 0.9717 - loss: 0.1074 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4591 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 293ms/step - accuracy: 0.9717 - loss: 0.1073 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4592 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 293ms/step - accuracy: 0.9718 - loss: 0.1073 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4592 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 293ms/step - accuracy: 0.9718 - loss: 0.1072 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4593 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 293ms/step - accuracy: 0.9718 - loss: 0.1071 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4593 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 293ms/step - accuracy: 0.9718 - loss: 0.1070 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4594 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 293ms/step - accuracy: 0.9718 - loss: 0.1069 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4594 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 293ms/step - accuracy: 0.9718 - loss: 0.1068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4594 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 293ms/step - accuracy: 0.9718 - loss: 0.1068 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4595 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 297ms/step - accuracy: 0.9734 - loss: 0.0969 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4643 - val_accuracy: 0.9608 - val_loss: 0.1670 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4779 Epoch 3/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9730 - loss: 0.0925 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4706  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 290ms/step - accuracy: 0.9723 - loss: 0.0937 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4709  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 291ms/step - accuracy: 0.9723 - loss: 0.0934 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4709  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9729 - loss: 0.0914 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4710  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9733 - loss: 0.0899 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4711  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9737 - loss: 0.0887 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4712  7/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9740 - loss: 0.0877 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4713  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9742 - loss: 0.0868 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4714  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9745 - loss: 0.0860 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4715  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9747 - loss: 0.0854 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4716  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9747 - loss: 0.0850 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4716  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9748 - loss: 0.0847 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4717  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9749 - loss: 0.0845 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4717  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9749 - loss: 0.0843 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4717  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9749 - loss: 0.0842 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4717  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9750 - loss: 0.0840 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4718  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9750 - loss: 0.0839 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4718  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9751 - loss: 0.0837 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4718  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9751 - loss: 0.0836 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4718  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9751 - loss: 0.0834 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4719  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9752 - loss: 0.0832 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4719  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9752 - loss: 0.0831 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4719  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9753 - loss: 0.0830 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4720  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 0.9753 - loss: 0.0829 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4720  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9753 - loss: 0.0828 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4720  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9753 - loss: 0.0827 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4720  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9753 - loss: 0.0827 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4720  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9753 - loss: 0.0826 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4720  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9754 - loss: 0.0825 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4721  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9754 - loss: 0.0825 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4721  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9754 - loss: 0.0824 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4721  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9754 - loss: 0.0823 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4721  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9754 - loss: 0.0822 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4721  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9754 - loss: 0.0821 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4721  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9755 - loss: 0.0821 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4722  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9755 - loss: 0.0820 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4722  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9755 - loss: 0.0820 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4722  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9755 - loss: 0.0819 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4722  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9755 - loss: 0.0819 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4722  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9755 - loss: 0.0818 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4722  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9755 - loss: 0.0818 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4723  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9755 - loss: 0.0817 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4723  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9755 - loss: 0.0817 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4723  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9756 - loss: 0.0816 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4723  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9756 - loss: 0.0816 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4723  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9756 - loss: 0.0815 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4723  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9756 - loss: 0.0814 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4724  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9756 - loss: 0.0814 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4724  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9756 - loss: 0.0814 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4724  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9756 - loss: 0.0813 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4724  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9756 - loss: 0.0813 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4724  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9756 - loss: 0.0812 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4724  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9756 - loss: 0.0812 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4724  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9757 - loss: 0.0811 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4725  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9757 - loss: 0.0811 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4725  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9757 - loss: 0.0811 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4725  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9757 - loss: 0.0810 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4725  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9757 - loss: 0.0810 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4725  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9757 - loss: 0.0809 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4725  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9757 - loss: 0.0809 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4725  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9757 - loss: 0.0808 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4726  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9757 - loss: 0.0808 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4726  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9757 - loss: 0.0808 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4726  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9757 - loss: 0.0807 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4726  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9758 - loss: 0.0807 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4726  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9758 - loss: 0.0807 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4726  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9758 - loss: 0.0806 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4726  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9758 - loss: 0.0806 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4727  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9758 - loss: 0.0806 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4727  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9758 - loss: 0.0805 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4727  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9758 - loss: 0.0805 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4727  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9758 - loss: 0.0805 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4727  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9758 - loss: 0.0804 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4727  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9758 - loss: 0.0804 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4727  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9758 - loss: 0.0804 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4728  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9758 - loss: 0.0803 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4728  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9758 - loss: 0.0803 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4728  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9758 - loss: 0.0803 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4728  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9759 - loss: 0.0802 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4728  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9759 - loss: 0.0802 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4728  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9759 - loss: 0.0802 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4728  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9759 - loss: 0.0801 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4728  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9759 - loss: 0.0801 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4729  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9759 - loss: 0.0801 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4729  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9759 - loss: 0.0801 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4729  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9759 - loss: 0.0800 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4729  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9759 - loss: 0.0800 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4729   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9759 - loss: 0.0800 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4729  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9759 - loss: 0.0799 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4729  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9759 - loss: 0.0799 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4730  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9759 - loss: 0.0799 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4730  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9759 - loss: 0.0799 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4730  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9759 - loss: 0.0798 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4730  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9760 - loss: 0.0798 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4730  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9760 - loss: 0.0798 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4730  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9760 - loss: 0.0797 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4730  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9760 - loss: 0.0797 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4730  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9760 - loss: 0.0797 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4731  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9760 - loss: 0.0796 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4731 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9760 - loss: 0.0796 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4731 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9760 - loss: 0.0796 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4731 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9760 - loss: 0.0796 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4731 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9760 - loss: 0.0795 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4731 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9760 - loss: 0.0795 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4731 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9760 - loss: 0.0795 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4731 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9760 - loss: 0.0794 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9760 - loss: 0.0794 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9760 - loss: 0.0794 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9760 - loss: 0.0794 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9760 - loss: 0.0793 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9760 - loss: 0.0793 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9761 - loss: 0.0793 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9761 - loss: 0.0793 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4732 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9761 - loss: 0.0792 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4733 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9761 - loss: 0.0792 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4733 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9761 - loss: 0.0792 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4733 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9761 - loss: 0.0791 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4733 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9761 - loss: 0.0791 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4733 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9761 - loss: 0.0791 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4733 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9761 - loss: 0.0791 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4733 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9768 - loss: 0.0758 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4748 - val_accuracy: 0.9604 - val_loss: 0.1641 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4892 Epoch 4/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9733 - loss: 0.0788 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4759  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9730 - loss: 0.0804 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4766  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9731 - loss: 0.0805 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4769  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9739 - loss: 0.0788 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4773  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9744 - loss: 0.0775 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4776  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9748 - loss: 0.0765 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4778  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9752 - loss: 0.0756 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4779  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9755 - loss: 0.0747 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4780  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9758 - loss: 0.0740 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4781  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9760 - loss: 0.0735 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9762 - loss: 0.0732 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9763 - loss: 0.0729 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9764 - loss: 0.0727 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9765 - loss: 0.0726 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9765 - loss: 0.0725 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9766 - loss: 0.0724 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9766 - loss: 0.0722 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9767 - loss: 0.0721 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9767 - loss: 0.0720 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9768 - loss: 0.0718 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9769 - loss: 0.0716 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9769 - loss: 0.0715 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9770 - loss: 0.0714 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9770 - loss: 0.0713 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9770 - loss: 0.0712 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9771 - loss: 0.0711 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9771 - loss: 0.0711 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9771 - loss: 0.0710 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9771 - loss: 0.0709 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9772 - loss: 0.0708 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9772 - loss: 0.0708 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9772 - loss: 0.0707 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9773 - loss: 0.0706 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9773 - loss: 0.0705 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9773 - loss: 0.0704 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9773 - loss: 0.0703 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9774 - loss: 0.0703 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9774 - loss: 0.0702 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4783  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9774 - loss: 0.0702 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9774 - loss: 0.0701 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9774 - loss: 0.0701 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9775 - loss: 0.0700 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9775 - loss: 0.0699 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9775 - loss: 0.0699 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9775 - loss: 0.0698 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9775 - loss: 0.0697 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9776 - loss: 0.0697 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9776 - loss: 0.0696 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9776 - loss: 0.0696 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9776 - loss: 0.0695 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4784  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9776 - loss: 0.0695 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9776 - loss: 0.0695 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9776 - loss: 0.0694 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9777 - loss: 0.0694 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9777 - loss: 0.0693 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9777 - loss: 0.0693 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9777 - loss: 0.0692 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9777 - loss: 0.0692 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9777 - loss: 0.0691 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9777 - loss: 0.0691 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9777 - loss: 0.0690 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9778 - loss: 0.0690 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4785  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9778 - loss: 0.0690 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9778 - loss: 0.0689 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9778 - loss: 0.0689 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9778 - loss: 0.0689 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9778 - loss: 0.0688 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9778 - loss: 0.0688 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9778 - loss: 0.0687 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9778 - loss: 0.0687 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9779 - loss: 0.0687 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9779 - loss: 0.0686 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9779 - loss: 0.0686 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9779 - loss: 0.0685 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9779 - loss: 0.0685 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9779 - loss: 0.0685 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9779 - loss: 0.0684 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9779 - loss: 0.0684 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9779 - loss: 0.0684 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9779 - loss: 0.0683 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9779 - loss: 0.0683 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9780 - loss: 0.0683 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9780 - loss: 0.0682 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9780 - loss: 0.0682 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9780 - loss: 0.0682 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4787  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9780 - loss: 0.0682 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9780 - loss: 0.0681 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9780 - loss: 0.0681 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9780 - loss: 0.0681 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9780 - loss: 0.0680 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9780 - loss: 0.0680 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9780 - loss: 0.0680 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9780 - loss: 0.0679 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9780 - loss: 0.0679 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9781 - loss: 0.0679 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9781 - loss: 0.0679 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9781 - loss: 0.0678 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9781 - loss: 0.0678 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4788  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9781 - loss: 0.0678 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9781 - loss: 0.0677 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9781 - loss: 0.0677 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9781 - loss: 0.0677 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9781 - loss: 0.0677 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9781 - loss: 0.0676 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9781 - loss: 0.0676 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9781 - loss: 0.0676 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9781 - loss: 0.0676 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9781 - loss: 0.0675 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9781 - loss: 0.0675 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9782 - loss: 0.0675 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9782 - loss: 0.0675 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9782 - loss: 0.0674 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4789 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9782 - loss: 0.0674 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4790 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9782 - loss: 0.0674 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4790 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9782 - loss: 0.0674 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4790 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9782 - loss: 0.0673 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4790 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9782 - loss: 0.0673 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4790 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9782 - loss: 0.0673 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4790 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9782 - loss: 0.0673 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4790 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9782 - loss: 0.0672 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4790 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9789 - loss: 0.0642 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4799 - val_accuracy: 0.9694 - val_loss: 0.1094 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4888 Epoch 5/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9761 - loss: 0.0680 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4777  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9756 - loss: 0.0694 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4782  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9758 - loss: 0.0694 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4786  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9764 - loss: 0.0679 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4791  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9769 - loss: 0.0668 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4794  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9773 - loss: 0.0659 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4797  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9776 - loss: 0.0651 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4799  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9779 - loss: 0.0643 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4801  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9782 - loss: 0.0636 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4802  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9784 - loss: 0.0632 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4804  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9785 - loss: 0.0629 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9786 - loss: 0.0626 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4805  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9787 - loss: 0.0624 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9787 - loss: 0.0623 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9788 - loss: 0.0623 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4806  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9788 - loss: 0.0621 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9789 - loss: 0.0620 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9789 - loss: 0.0619 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9789 - loss: 0.0618 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9790 - loss: 0.0617 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9790 - loss: 0.0616 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4808  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9791 - loss: 0.0615 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9791 - loss: 0.0614 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9792 - loss: 0.0613 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9792 - loss: 0.0613 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4809  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9792 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9792 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9792 - loss: 0.0612 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9792 - loss: 0.0611 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9793 - loss: 0.0611 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9793 - loss: 0.0610 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9793 - loss: 0.0610 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4810  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9793 - loss: 0.0609 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4811  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9793 - loss: 0.0609 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4811  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9794 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4811  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9794 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4811  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9794 - loss: 0.0608 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4811  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9794 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4811  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 0.9794 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4811  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 0.9794 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 0.9794 - loss: 0.0607 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9794 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9795 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9795 - loss: 0.0606 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9795 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9795 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9795 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9795 - loss: 0.0604 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9795 - loss: 0.0604 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4812  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9795 - loss: 0.0604 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9795 - loss: 0.0604 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9795 - loss: 0.0603 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9796 - loss: 0.0603 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9796 - loss: 0.0603 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9796 - loss: 0.0603 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9796 - loss: 0.0602 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9796 - loss: 0.0602 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9796 - loss: 0.0602 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9796 - loss: 0.0601 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9796 - loss: 0.0601 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9796 - loss: 0.0601 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9796 - loss: 0.0601 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4813  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9796 - loss: 0.0601 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9796 - loss: 0.0600 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9797 - loss: 0.0600 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.9797 - loss: 0.0600 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.9797 - loss: 0.0600 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.9797 - loss: 0.0599 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  69/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9797 - loss: 0.0599 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9797 - loss: 0.0599 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9797 - loss: 0.0598 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9797 - loss: 0.0598 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 293ms/step - accuracy: 0.9797 - loss: 0.0598 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 293ms/step - accuracy: 0.9797 - loss: 0.0598 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 293ms/step - accuracy: 0.9797 - loss: 0.0597 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9797 - loss: 0.0597 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9797 - loss: 0.0597 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9797 - loss: 0.0597 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9798 - loss: 0.0597 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9798 - loss: 0.0596 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9798 - loss: 0.0596 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9798 - loss: 0.0596 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9798 - loss: 0.0595 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9798 - loss: 0.0595 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9798 - loss: 0.0595 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  86/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9798 - loss: 0.0595 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815   87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 294ms/step - accuracy: 0.9798 - loss: 0.0595 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9798 - loss: 0.0594 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9798 - loss: 0.0594 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9798 - loss: 0.0594 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9798 - loss: 0.0594 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4815  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9798 - loss: 0.0593 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9798 - loss: 0.0593 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9799 - loss: 0.0593 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9799 - loss: 0.0593 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 294ms/step - accuracy: 0.9799 - loss: 0.0592 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9799 - loss: 0.0592 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9799 - loss: 0.0592 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 294ms/step - accuracy: 0.9799 - loss: 0.0592 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9799 - loss: 0.0591 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9799 - loss: 0.0591 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9799 - loss: 0.0591 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 103/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9799 - loss: 0.0591 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9799 - loss: 0.0591 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9799 - loss: 0.0590 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9799 - loss: 0.0590 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9799 - loss: 0.0590 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9799 - loss: 0.0590 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9799 - loss: 0.0589 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9799 - loss: 0.0589 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9799 - loss: 0.0589 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9800 - loss: 0.0589 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9800 - loss: 0.0589 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9800 - loss: 0.0588 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9800 - loss: 0.0588 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9800 - loss: 0.0588 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9800 - loss: 0.0588 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9800 - loss: 0.0587 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9800 - loss: 0.0587 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9800 - loss: 0.0587 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4817 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 0.9806 - loss: 0.0562 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4824 - val_accuracy: 0.9733 - val_loss: 0.0872 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4883 Epoch 6/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9770 - loss: 0.0625 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4794  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9769 - loss: 0.0631 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4797  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9771 - loss: 0.0629 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4801  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9777 - loss: 0.0614 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4807  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9782 - loss: 0.0605 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4811  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9785 - loss: 0.0597 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4814  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9788 - loss: 0.0590 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4816  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9791 - loss: 0.0583 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4819  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9793 - loss: 0.0577 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4821  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9795 - loss: 0.0573 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4822  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9796 - loss: 0.0570 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4823  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9797 - loss: 0.0568 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4824  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9798 - loss: 0.0566 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4825  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9798 - loss: 0.0565 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4825  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9798 - loss: 0.0565 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4826  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9799 - loss: 0.0564 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4826  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9799 - loss: 0.0562 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9799 - loss: 0.0561 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9800 - loss: 0.0560 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4827  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9800 - loss: 0.0559 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9801 - loss: 0.0558 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9801 - loss: 0.0557 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4828  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9802 - loss: 0.0556 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9802 - loss: 0.0555 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9802 - loss: 0.0554 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9802 - loss: 0.0554 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9803 - loss: 0.0553 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9803 - loss: 0.0553 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9803 - loss: 0.0552 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9803 - loss: 0.0552 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9803 - loss: 0.0551 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9804 - loss: 0.0551 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4830  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9804 - loss: 0.0550 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9804 - loss: 0.0549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9804 - loss: 0.0549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9805 - loss: 0.0549 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9805 - loss: 0.0548 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9805 - loss: 0.0548 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9805 - loss: 0.0548 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9805 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9805 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4831  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9805 - loss: 0.0547 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9805 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9806 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9806 - loss: 0.0546 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9806 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9806 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9806 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9806 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9806 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9806 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9806 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9806 - loss: 0.0544 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9806 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9807 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4832  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9807 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9807 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9807 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9807 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9807 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9807 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9807 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9807 - loss: 0.0542 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9807 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9807 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9807 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9807 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9807 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9807 - loss: 0.0541 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9807 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9808 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9808 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9808 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9808 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9808 - loss: 0.0540 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9808 - loss: 0.0539 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9808 - loss: 0.0539 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9808 - loss: 0.0539 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9808 - loss: 0.0539 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9808 - loss: 0.0539 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9808 - loss: 0.0539 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9808 - loss: 0.0539 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9808 - loss: 0.0538 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9808 - loss: 0.0538 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9808 - loss: 0.0538 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9808 - loss: 0.0538 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9808 - loss: 0.0538 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9808 - loss: 0.0538 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9808 - loss: 0.0538 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9808 - loss: 0.0537 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9808 - loss: 0.0537 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9808 - loss: 0.0537 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9809 - loss: 0.0537 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9809 - loss: 0.0537 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9809 - loss: 0.0537 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9809 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9809 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9809 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9809 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9809 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9809 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9809 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9809 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9809 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9809 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9809 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9809 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9809 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9809 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9809 - loss: 0.0535 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9809 - loss: 0.0534 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9809 - loss: 0.0534 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9809 - loss: 0.0534 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9809 - loss: 0.0534 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9809 - loss: 0.0534 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9809 - loss: 0.0534 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9809 - loss: 0.0534 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9810 - loss: 0.0533 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9810 - loss: 0.0533 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4836 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9810 - loss: 0.0533 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4836 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 0.9814 - loss: 0.0516 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840 - val_accuracy: 0.9761 - val_loss: 0.0724 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4851 Epoch 7/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 0.9789 - loss: 0.0562 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4837  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9781 - loss: 0.0576 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4834  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9781 - loss: 0.0578 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.9786 - loss: 0.0566 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4835  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9790 - loss: 0.0557 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4837  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9793 - loss: 0.0551 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4839  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9795 - loss: 0.0545 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9798 - loss: 0.0539 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4841  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9801 - loss: 0.0533 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9802 - loss: 0.0529 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9804 - loss: 0.0527 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4843  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9805 - loss: 0.0525 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9805 - loss: 0.0523 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9806 - loss: 0.0522 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9806 - loss: 0.0522 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9807 - loss: 0.0521 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9807 - loss: 0.0520 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9807 - loss: 0.0519 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9808 - loss: 0.0519 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 292ms/step - accuracy: 0.9808 - loss: 0.0518 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  21/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9809 - loss: 0.0517 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9809 - loss: 0.0516 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9810 - loss: 0.0515 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 292ms/step - accuracy: 0.9810 - loss: 0.0514 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4845  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 292ms/step - accuracy: 0.9810 - loss: 0.0514 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 292ms/step - accuracy: 0.9810 - loss: 0.0513 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 292ms/step - accuracy: 0.9810 - loss: 0.0513 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  28/120 ━━━━━━━━━━━━━━━━━━━━ 26s 292ms/step - accuracy: 0.9811 - loss: 0.0513 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 292ms/step - accuracy: 0.9811 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 0.9811 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 292ms/step - accuracy: 0.9811 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9811 - loss: 0.0511 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9812 - loss: 0.0511 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9812 - loss: 0.0510 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 292ms/step - accuracy: 0.9812 - loss: 0.0510 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 292ms/step - accuracy: 0.9812 - loss: 0.0509 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 292ms/step - accuracy: 0.9812 - loss: 0.0509 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  38/120 ━━━━━━━━━━━━━━━━━━━━ 23s 292ms/step - accuracy: 0.9812 - loss: 0.0509 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 292ms/step - accuracy: 0.9812 - loss: 0.0508 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 292ms/step - accuracy: 0.9813 - loss: 0.0508 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 292ms/step - accuracy: 0.9813 - loss: 0.0508 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 292ms/step - accuracy: 0.9813 - loss: 0.0507 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 292ms/step - accuracy: 0.9813 - loss: 0.0507 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 292ms/step - accuracy: 0.9813 - loss: 0.0507 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  45/120 ━━━━━━━━━━━━━━━━━━━━ 21s 292ms/step - accuracy: 0.9813 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 292ms/step - accuracy: 0.9813 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9814 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9814 - loss: 0.0505 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9814 - loss: 0.0505 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9814 - loss: 0.0505 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9814 - loss: 0.0505 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9814 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9814 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9814 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9814 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9814 - loss: 0.0503 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9815 - loss: 0.0503 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9815 - loss: 0.0503 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9815 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9815 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9815 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  62/120 ━━━━━━━━━━━━━━━━━━━━ 16s 293ms/step - accuracy: 0.9815 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 293ms/step - accuracy: 0.9815 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 293ms/step - accuracy: 0.9815 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 293ms/step - accuracy: 0.9815 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 293ms/step - accuracy: 0.9815 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 293ms/step - accuracy: 0.9815 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 293ms/step - accuracy: 0.9815 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  69/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9815 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9816 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9816 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 293ms/step - accuracy: 0.9816 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 293ms/step - accuracy: 0.9816 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 293ms/step - accuracy: 0.9816 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 293ms/step - accuracy: 0.9816 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9816 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9816 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9816 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 293ms/step - accuracy: 0.9816 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9816 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9816 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 293ms/step - accuracy: 0.9816 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9817 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9817 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 293ms/step - accuracy: 0.9817 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  86/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9817 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849   87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9817 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9817 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 293ms/step - accuracy: 0.9817 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9817 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9817 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 293ms/step - accuracy: 0.9817 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9817 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9817 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9817 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 293ms/step - accuracy: 0.9817 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 293ms/step - accuracy: 0.9817 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 293ms/step - accuracy: 0.9817 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 293ms/step - accuracy: 0.9817 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9818 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9818 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 294ms/step - accuracy: 0.9818 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 103/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9818 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9818 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9818 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 294ms/step - accuracy: 0.9818 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9818 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9818 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 294ms/step - accuracy: 0.9818 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9818 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9818 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9818 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 294ms/step - accuracy: 0.9818 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9818 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9818 - loss: 0.0491 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 294ms/step - accuracy: 0.9818 - loss: 0.0491 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9818 - loss: 0.0491 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9818 - loss: 0.0491 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9818 - loss: 0.0491 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 294ms/step - accuracy: 0.9819 - loss: 0.0491 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 298ms/step - accuracy: 0.9824 - loss: 0.0471 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854 - val_accuracy: 0.9760 - val_loss: 0.0746 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4874 Epoch 8/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 294ms/step - accuracy: 0.9798 - loss: 0.0517 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.9793 - loss: 0.0528 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9794 - loss: 0.0524 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9800 - loss: 0.0511 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9804 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9808 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9810 - loss: 0.0486 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4852  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9813 - loss: 0.0480 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9816 - loss: 0.0474 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9817 - loss: 0.0470 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9819 - loss: 0.0468 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9820 - loss: 0.0465 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9821 - loss: 0.0463 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9821 - loss: 0.0463 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9821 - loss: 0.0462 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9822 - loss: 0.0461 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9822 - loss: 0.0460 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9823 - loss: 0.0459 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9823 - loss: 0.0458 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9823 - loss: 0.0457 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9824 - loss: 0.0456 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9824 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9825 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9825 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9825 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9825 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9826 - loss: 0.0453 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9826 - loss: 0.0452 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9826 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9826 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9826 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9827 - loss: 0.0451 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9827 - loss: 0.0450 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9827 - loss: 0.0449 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9827 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9827 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9828 - loss: 0.0448 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9828 - loss: 0.0447 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9828 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9828 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9828 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9828 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9828 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9828 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9829 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9829 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9829 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9829 - loss: 0.0446 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9829 - loss: 0.0445 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9829 - loss: 0.0444 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9829 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9830 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9830 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9830 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9830 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9830 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9830 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9830 - loss: 0.0443 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4863 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9831 - loss: 0.0442 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4864 - val_accuracy: 0.9759 - val_loss: 0.0925 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4907 Epoch 9/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9792 - loss: 0.0537 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9787 - loss: 0.0563 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.9788 - loss: 0.0564 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4829  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.9793 - loss: 0.0551 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4833  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9797 - loss: 0.0543 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4837  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9800 - loss: 0.0536 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4840  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9803 - loss: 0.0530 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4842  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9805 - loss: 0.0525 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4844  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9808 - loss: 0.0520 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4846  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9809 - loss: 0.0517 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4847  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 295ms/step - accuracy: 0.9810 - loss: 0.0515 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9811 - loss: 0.0513 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 295ms/step - accuracy: 0.9811 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9811 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9811 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9812 - loss: 0.0512 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4848  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9812 - loss: 0.0511 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9812 - loss: 0.0510 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9812 - loss: 0.0509 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9813 - loss: 0.0508 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9813 - loss: 0.0507 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4849  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9814 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9814 - loss: 0.0506 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9814 - loss: 0.0505 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9814 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9814 - loss: 0.0504 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4850  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9815 - loss: 0.0503 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9815 - loss: 0.0503 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9815 - loss: 0.0502 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9815 - loss: 0.0501 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9815 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9816 - loss: 0.0500 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4851  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9816 - loss: 0.0499 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4852  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9816 - loss: 0.0498 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4852  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 296ms/step - accuracy: 0.9816 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4852  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9817 - loss: 0.0497 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4852  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9817 - loss: 0.0496 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4852  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 296ms/step - accuracy: 0.9817 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4852  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9817 - loss: 0.0495 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9817 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9817 - loss: 0.0494 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9818 - loss: 0.0493 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9818 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9818 - loss: 0.0492 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4853  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9818 - loss: 0.0491 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9818 - loss: 0.0490 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9819 - loss: 0.0489 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9819 - loss: 0.0489 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9819 - loss: 0.0488 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9819 - loss: 0.0488 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9819 - loss: 0.0487 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4854  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9819 - loss: 0.0486 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9819 - loss: 0.0486 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9820 - loss: 0.0485 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9820 - loss: 0.0485 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9820 - loss: 0.0484 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9820 - loss: 0.0483 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9820 - loss: 0.0483 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9820 - loss: 0.0482 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4855  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9821 - loss: 0.0481 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9821 - loss: 0.0481 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9821 - loss: 0.0480 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9821 - loss: 0.0480 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9821 - loss: 0.0479 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9821 - loss: 0.0479 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9822 - loss: 0.0478 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4856  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9822 - loss: 0.0478 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9822 - loss: 0.0477 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9822 - loss: 0.0476 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9822 - loss: 0.0476 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9822 - loss: 0.0475 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9822 - loss: 0.0475 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9823 - loss: 0.0474 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9823 - loss: 0.0474 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9823 - loss: 0.0473 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4857  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9823 - loss: 0.0473 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9823 - loss: 0.0472 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9823 - loss: 0.0472 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 296ms/step - accuracy: 0.9823 - loss: 0.0471 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9823 - loss: 0.0471 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9824 - loss: 0.0470 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 296ms/step - accuracy: 0.9824 - loss: 0.0470 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9824 - loss: 0.0469 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4858  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9824 - loss: 0.0469 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9824 - loss: 0.0468 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9824 - loss: 0.0468 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9824 - loss: 0.0467 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9824 - loss: 0.0467 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9825 - loss: 0.0466 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9825 - loss: 0.0466 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9825 - loss: 0.0465 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9825 - loss: 0.0465 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9825 - loss: 0.0465 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4859  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9825 - loss: 0.0464 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9825 - loss: 0.0464 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9825 - loss: 0.0463 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9826 - loss: 0.0463 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9826 - loss: 0.0462 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9826 - loss: 0.0462 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9826 - loss: 0.0462 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9826 - loss: 0.0461 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9826 - loss: 0.0461 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9826 - loss: 0.0460 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4860 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9826 - loss: 0.0460 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9826 - loss: 0.0460 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9826 - loss: 0.0459 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9827 - loss: 0.0459 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9827 - loss: 0.0458 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9827 - loss: 0.0458 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9827 - loss: 0.0458 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9827 - loss: 0.0457 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9827 - loss: 0.0457 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9827 - loss: 0.0457 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9827 - loss: 0.0456 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9827 - loss: 0.0456 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4861 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9827 - loss: 0.0456 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9828 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9828 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9828 - loss: 0.0455 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9828 - loss: 0.0454 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4862 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 0.9839 - loss: 0.0413 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4872 - val_accuracy: 0.9733 - val_loss: 0.0733 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4829 Epoch 10/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 0.9827 - loss: 0.0419 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4870  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9823 - loss: 0.0425 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4869  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9824 - loss: 0.0421 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4870  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 294ms/step - accuracy: 0.9829 - loss: 0.0410 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4873  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9832 - loss: 0.0402 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4874  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9835 - loss: 0.0397 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9837 - loss: 0.0392 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4877  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9839 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4878  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9841 - loss: 0.0383 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4879  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9843 - loss: 0.0380 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4879  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9844 - loss: 0.0378 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9845 - loss: 0.0376 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9845 - loss: 0.0375 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9846 - loss: 0.0374 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9846 - loss: 0.0374 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4880  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9846 - loss: 0.0373 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9847 - loss: 0.0372 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9847 - loss: 0.0372 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9847 - loss: 0.0371 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9848 - loss: 0.0370 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9848 - loss: 0.0369 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 0.9848 - loss: 0.0369 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 0.9849 - loss: 0.0368 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 0.9849 - loss: 0.0368 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 0.9849 - loss: 0.0367 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 0.9849 - loss: 0.0367 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 293ms/step - accuracy: 0.9849 - loss: 0.0367 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  28/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 0.9849 - loss: 0.0367 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 0.9850 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 293ms/step - accuracy: 0.9850 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9850 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9850 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9850 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 293ms/step - accuracy: 0.9850 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 0.9850 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9850 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9850 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9851 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 0.9851 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9851 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9851 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9852 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9852 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9852 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9852 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9852 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 296ms/step - accuracy: 0.9852 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9852 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9852 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9853 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9853 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9853 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9853 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9856 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887 - val_accuracy: 0.9765 - val_loss: 0.0736 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4890 Epoch 11/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9835 - loss: 0.0399 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9830 - loss: 0.0408 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4875  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9831 - loss: 0.0406 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4876  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9835 - loss: 0.0396 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4879  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9838 - loss: 0.0389 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9840 - loss: 0.0384 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4883  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9842 - loss: 0.0380 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9844 - loss: 0.0376 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4885  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9846 - loss: 0.0372 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9847 - loss: 0.0370 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9848 - loss: 0.0368 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9849 - loss: 0.0366 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4887  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9849 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9849 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9850 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9850 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9850 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9851 - loss: 0.0362 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9851 - loss: 0.0361 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9851 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9852 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9852 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9852 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9853 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9853 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9853 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9853 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9853 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9853 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9853 - loss: 0.0356 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9854 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9854 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9854 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9854 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9854 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9854 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9855 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9855 - loss: 0.0353 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9855 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9855 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9855 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9855 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9855 - loss: 0.0351 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9855 - loss: 0.0351 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9856 - loss: 0.0351 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9856 - loss: 0.0350 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9856 - loss: 0.0350 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9856 - loss: 0.0350 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9856 - loss: 0.0349 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9856 - loss: 0.0349 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9856 - loss: 0.0349 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9856 - loss: 0.0349 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9856 - loss: 0.0348 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9857 - loss: 0.0348 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9857 - loss: 0.0348 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9857 - loss: 0.0348 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9857 - loss: 0.0347 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9857 - loss: 0.0347 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9857 - loss: 0.0347 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9857 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9857 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9857 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9857 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9857 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9858 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9858 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9858 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9858 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9858 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9858 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9858 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9858 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9858 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9858 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9858 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9859 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9859 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9859 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9859 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9859 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9859 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9859 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9859 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9859 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9859 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9859 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9860 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9860 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9860 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9860 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9860 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9860 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9860 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9861 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9861 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9861 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9861 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9861 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9866 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896 - val_accuracy: 0.9764 - val_loss: 0.0795 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4901 Epoch 12/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9844 - loss: 0.0381 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9837 - loss: 0.0391 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4881  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9838 - loss: 0.0388 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4882  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9842 - loss: 0.0377 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4884  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9845 - loss: 0.0370 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4886  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9848 - loss: 0.0364 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9850 - loss: 0.0359 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9851 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9853 - loss: 0.0351 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4891  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9854 - loss: 0.0349 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9855 - loss: 0.0347 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9855 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9856 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9856 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9856 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9857 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9857 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9857 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9857 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9858 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9858 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9858 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9859 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9859 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9859 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9859 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9859 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9859 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9860 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9860 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9860 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9860 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9860 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9861 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9861 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9861 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9861 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9861 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9861 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9861 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9861 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9861 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9862 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9862 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9862 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9862 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9862 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9862 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9862 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9862 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9862 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9863 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9863 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9863 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9863 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9863 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9863 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9863 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9864 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9864 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9864 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9864 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9864 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9865 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9865 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9865 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9866 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9866 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9866 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901 - val_accuracy: 0.9701 - val_loss: 0.0920 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4875 Epoch 13/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9834 - loss: 0.0393 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9836 - loss: 0.0387 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9839 - loss: 0.0379 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4893  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9844 - loss: 0.0368 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9846 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9848 - loss: 0.0358 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9850 - loss: 0.0354 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9852 - loss: 0.0350 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9854 - loss: 0.0346 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9855 - loss: 0.0344 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9856 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9857 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9857 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9858 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9858 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9858 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9859 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9859 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 297ms/step - accuracy: 0.9860 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9860 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9861 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9861 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9861 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9862 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9862 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9862 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9862 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9863 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9863 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9864 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9864 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9865 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9865 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9866 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9866 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9866 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9867 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9867 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9867 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9867 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9867 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9867 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9867 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9867 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9867 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9868 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9868 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9868 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9868 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9868 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9868 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9868 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9868 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9868 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9868 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9868 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9868 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9868 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 296ms/step - accuracy: 0.9869 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9869 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 296ms/step - accuracy: 0.9869 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9869 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9869 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9869 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9869 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9869 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9870 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9870 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9870 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9870 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9874 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 - val_accuracy: 0.9752 - val_loss: 0.0820 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4899 Epoch 14/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9863 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9860 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9860 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9863 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9865 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9867 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9868 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9870 - loss: 0.0308 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9871 - loss: 0.0305 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9872 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9872 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9873 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9873 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9874 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9874 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9875 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9875 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9875 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9877 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9877 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9878 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9878 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908 - val_accuracy: 0.9746 - val_loss: 0.0916 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4902 Epoch 15/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9848 - loss: 0.0348 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4889  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9843 - loss: 0.0363 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9842 - loss: 0.0365 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4888  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9845 - loss: 0.0360 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4890  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9846 - loss: 0.0357 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4892  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9848 - loss: 0.0355 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4894  7/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9849 - loss: 0.0352 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4895  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9851 - loss: 0.0348 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4896  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9853 - loss: 0.0345 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4897  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9854 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9854 - loss: 0.0343 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9855 - loss: 0.0342 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9855 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  14/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9855 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9856 - loss: 0.0341 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9856 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 292ms/step - accuracy: 0.9856 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9856 - loss: 0.0340 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9856 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9857 - loss: 0.0339 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 293ms/step - accuracy: 0.9857 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 293ms/step - accuracy: 0.9857 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9857 - loss: 0.0338 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9857 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9858 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9858 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9858 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9858 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9858 - loss: 0.0337 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9858 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9858 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9858 - loss: 0.0336 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9859 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9859 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9859 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9859 - loss: 0.0335 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9859 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9859 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9859 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9859 - loss: 0.0334 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9860 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9860 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9860 - loss: 0.0333 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9860 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9860 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9860 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4899  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9861 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9861 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9861 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9861 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9861 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9861 - loss: 0.0330 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9861 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9862 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9862 - loss: 0.0329 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9862 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9862 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9862 - loss: 0.0328 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9862 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9862 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9863 - loss: 0.0327 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9863 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9863 - loss: 0.0326 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9863 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9863 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9863 - loss: 0.0325 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9864 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9864 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9864 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9864 - loss: 0.0323 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9864 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9865 - loss: 0.0322 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9865 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9865 - loss: 0.0321 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9865 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9865 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9865 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9866 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9866 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9866 - loss: 0.0319 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9866 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9866 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9866 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9866 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9867 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9867 - loss: 0.0317 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9867 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9867 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9867 - loss: 0.0316 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9867 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9867 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9868 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9868 - loss: 0.0315 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9868 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9868 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9868 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9868 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9868 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9868 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9868 - loss: 0.0313 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9869 - loss: 0.0312 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9869 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9869 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9869 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9869 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9869 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9869 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9870 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9870 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9870 - loss: 0.0310 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9870 - loss: 0.0309 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9870 - loss: 0.0309 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9870 - loss: 0.0309 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9870 - loss: 0.0309 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 0.9879 - loss: 0.0286 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911 - val_accuracy: 0.9772 - val_loss: 0.0848 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4918 Epoch 16/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9866 - loss: 0.0320 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4901  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9859 - loss: 0.0332 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9859 - loss: 0.0331 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4898  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9862 - loss: 0.0324 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4900  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9864 - loss: 0.0318 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9866 - loss: 0.0314 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9867 - loss: 0.0311 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9868 - loss: 0.0308 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4903  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9869 - loss: 0.0306 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9870 - loss: 0.0305 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9870 - loss: 0.0304 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9871 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9871 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4905  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9871 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9871 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9872 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9872 - loss: 0.0302 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9872 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9872 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 296ms/step - accuracy: 0.9872 - loss: 0.0301 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9873 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9873 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9873 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9874 - loss: 0.0299 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9874 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9874 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9874 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 295ms/step - accuracy: 0.9874 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9875 - loss: 0.0298 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 295ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 295ms/step - accuracy: 0.9875 - loss: 0.0297 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9875 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9875 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 295ms/step - accuracy: 0.9875 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9875 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9876 - loss: 0.0296 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 295ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9876 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9876 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9876 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9876 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9876 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9876 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9876 - loss: 0.0294 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9877 - loss: 0.0293 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9877 - loss: 0.0292 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9877 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9877 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9878 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9878 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9878 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9878 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9878 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9878 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9878 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9878 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9879 - loss: 0.0289 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9879 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9879 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9879 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9879 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9879 - loss: 0.0287 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 0.9883 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913 - val_accuracy: 0.9764 - val_loss: 0.0954 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4924 Epoch 17/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9875 - loss: 0.0290 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9869 - loss: 0.0303 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 295ms/step - accuracy: 0.9868 - loss: 0.0305 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4902  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9871 - loss: 0.0300 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4904  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9873 - loss: 0.0295 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4906  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9875 - loss: 0.0291 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4907  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9877 - loss: 0.0288 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4908  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9879 - loss: 0.0284 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4909  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9880 - loss: 0.0281 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4910  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9881 - loss: 0.0279 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9882 - loss: 0.0278 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4911  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9883 - loss: 0.0276 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 297ms/step - accuracy: 0.9883 - loss: 0.0275 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9884 - loss: 0.0274 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4912  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9884 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9884 - loss: 0.0273 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9885 - loss: 0.0272 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9885 - loss: 0.0271 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9885 - loss: 0.0270 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4913  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9886 - loss: 0.0269 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9886 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 297ms/step - accuracy: 0.9886 - loss: 0.0268 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9887 - loss: 0.0267 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9887 - loss: 0.0266 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4914  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 297ms/step - accuracy: 0.9887 - loss: 0.0266 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 297ms/step - accuracy: 0.9887 - loss: 0.0265 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9888 - loss: 0.0265 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9888 - loss: 0.0265 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9888 - loss: 0.0264 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9888 - loss: 0.0264 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9888 - loss: 0.0263 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 297ms/step - accuracy: 0.9889 - loss: 0.0263 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4915  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9889 - loss: 0.0262 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9889 - loss: 0.0262 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 297ms/step - accuracy: 0.9889 - loss: 0.0261 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9890 - loss: 0.0261 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9890 - loss: 0.0260 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9890 - loss: 0.0260 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 297ms/step - accuracy: 0.9890 - loss: 0.0260 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9890 - loss: 0.0259 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9890 - loss: 0.0259 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 297ms/step - accuracy: 0.9891 - loss: 0.0258 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9891 - loss: 0.0258 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9891 - loss: 0.0258 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 297ms/step - accuracy: 0.9891 - loss: 0.0257 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9891 - loss: 0.0257 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9891 - loss: 0.0257 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9892 - loss: 0.0256 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 297ms/step - accuracy: 0.9892 - loss: 0.0256 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9892 - loss: 0.0256 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9892 - loss: 0.0255 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 297ms/step - accuracy: 0.9892 - loss: 0.0255 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9892 - loss: 0.0255 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9892 - loss: 0.0255 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9892 - loss: 0.0254 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 297ms/step - accuracy: 0.9893 - loss: 0.0254 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9893 - loss: 0.0254 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9893 - loss: 0.0253 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 297ms/step - accuracy: 0.9893 - loss: 0.0253 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9893 - loss: 0.0253 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9893 - loss: 0.0253 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 297ms/step - accuracy: 0.9893 - loss: 0.0252 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9893 - loss: 0.0252 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9893 - loss: 0.0252 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9894 - loss: 0.0252 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9894 - loss: 0.0252 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9894 - loss: 0.0251 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9894 - loss: 0.0251 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9894 - loss: 0.0251 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9894 - loss: 0.0251 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9894 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9894 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9894 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9894 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9895 - loss: 0.0250 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9895 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9895 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9895 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9895 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9895 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9895 - loss: 0.0249 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9895 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9895 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9895 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9895 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9895 - loss: 0.0248 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9896 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9896 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9896 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9896 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9896 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9896 - loss: 0.0247 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9896 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9896 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9896 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9896 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9896 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9896 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9896 - loss: 0.0246 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9896 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9897 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9897 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9897 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9897 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9897 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9897 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9897 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9897 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9897 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9897 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9897 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9897 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9897 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9897 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9897 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9897 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9898 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9898 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9898 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9898 - loss: 0.0243 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927 - val_accuracy: 0.9758 - val_loss: 0.0946 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4927 Epoch 18/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9896 - loss: 0.0238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9895 - loss: 0.0244 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 296ms/step - accuracy: 0.9894 - loss: 0.0245 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4916  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9896 - loss: 0.0241 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4917  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 297ms/step - accuracy: 0.9898 - loss: 0.0238 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4918  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 297ms/step - accuracy: 0.9899 - loss: 0.0235 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4919  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9900 - loss: 0.0233 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4920  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9901 - loss: 0.0231 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4921  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9902 - loss: 0.0229 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4922  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9903 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 297ms/step - accuracy: 0.9903 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9904 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9904 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9904 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 296ms/step - accuracy: 0.9904 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9904 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 296ms/step - accuracy: 0.9904 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9904 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9906 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9906 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9906 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9906 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9906 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9906 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9906 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9906 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9905 - loss: 0.0224 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 295ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 294ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 294ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9905 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9905 - loss: 0.0226 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 295ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 295ms/step - accuracy: 0.9905 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9904 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9904 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 295ms/step - accuracy: 0.9904 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9904 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9904 - loss: 0.0227 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 295ms/step - accuracy: 0.9904 - loss: 0.0228 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 299ms/step - accuracy: 0.9907 - loss: 0.0222 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4930 - val_accuracy: 0.9770 - val_loss: 0.0959 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4935 Epoch 19/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9919 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 297ms/step - accuracy: 0.9914 - loss: 0.0206 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4923  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9913 - loss: 0.0208 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4924  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9914 - loss: 0.0206 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4926  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9915 - loss: 0.0204 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9916 - loss: 0.0202 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4929  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9917 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4931  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4932  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9918 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4933  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4933  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9920 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9921 - loss: 0.0191 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9920 - loss: 0.0192 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9920 - loss: 0.0193 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9920 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9920 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9920 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9919 - loss: 0.0194 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9919 - loss: 0.0195 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9919 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9918 - loss: 0.0196 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9918 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937 - val_accuracy: 0.9764 - val_loss: 0.1049 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4939 Epoch 20/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9907 - loss: 0.0223 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9906 - loss: 0.0225 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9907 - loss: 0.0222 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4925  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9910 - loss: 0.0216 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4927  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9911 - loss: 0.0213 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4928  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9912 - loss: 0.0210 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4929  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9913 - loss: 0.0208 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4930  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9914 - loss: 0.0206 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4931  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 298ms/step - accuracy: 0.9914 - loss: 0.0205 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4932  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9915 - loss: 0.0203 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4933  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9915 - loss: 0.0203 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4933  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 298ms/step - accuracy: 0.9915 - loss: 0.0202 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9915 - loss: 0.0202 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9915 - loss: 0.0201 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9916 - loss: 0.0201 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9916 - loss: 0.0201 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4934  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9916 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 298ms/step - accuracy: 0.9917 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9917 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9917 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4935  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 298ms/step - accuracy: 0.9917 - loss: 0.0198 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - 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━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9918 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9918 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9918 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9918 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9917 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - 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━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9917 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9917 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9917 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9916 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9916 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9916 - loss: 0.0199 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - 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━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9916 - loss: 0.0200 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4936 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9918 - loss: 0.0197 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4937 - val_accuracy: 0.9768 - val_loss: 0.1085 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4949 Epoch 21/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 299ms/step - accuracy: 0.9926 - loss: 0.0182 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 301ms/step - accuracy: 0.9924 - loss: 0.0185 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4939  3/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9925 - loss: 0.0184 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4938  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 0.9926 - loss: 0.0180 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4939  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 301ms/step - accuracy: 0.9927 - loss: 0.0177 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4940  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 300ms/step - accuracy: 0.9928 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 300ms/step - accuracy: 0.9929 - loss: 0.0173 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4941  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 300ms/step - accuracy: 0.9930 - loss: 0.0171 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9930 - loss: 0.0169 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9931 - loss: 0.0168 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9931 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9932 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9932 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9932 - loss: 0.0166 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9932 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 298ms/step - accuracy: 0.9932 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9933 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9933 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 298ms/step - accuracy: 0.9933 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9933 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9933 - loss: 0.0163 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9934 - loss: 0.0161 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9934 - loss: 0.0161 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9934 - loss: 0.0161 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9934 - loss: 0.0161 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9934 - loss: 0.0160 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9934 - loss: 0.0160 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9935 - loss: 0.0160 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9935 - loss: 0.0160 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 299ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9936 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  53/120 ━━━━━━━━━━━━━━━━━━━━ 20s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 299ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 299ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  63/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  73/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  83/120 ━━━━━━━━━━━━━━━━━━━━ 11s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 298ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9936 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9936 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 298ms/step - accuracy: 0.9936 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9935 - loss: 0.0158 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 298ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 302ms/step - accuracy: 0.9933 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947 - val_accuracy: 0.9767 - val_loss: 0.1070 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4947 Epoch 22/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 300ms/step - accuracy: 0.9928 - loss: 0.0172 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  2/120 ━━━━━━━━━━━━━━━━━━━━ 35s 298ms/step - accuracy: 0.9927 - loss: 0.0175 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 298ms/step - accuracy: 0.9928 - loss: 0.0174 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9930 - loss: 0.0170 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  5/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9931 - loss: 0.0167 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  6/120 ━━━━━━━━━━━━━━━━━━━━ 34s 299ms/step - accuracy: 0.9932 - loss: 0.0165 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9933 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  8/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9934 - loss: 0.0160 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  9/120 ━━━━━━━━━━━━━━━━━━━━ 33s 299ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9935 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9936 - loss: 0.0156 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  12/120 ━━━━━━━━━━━━━━━━━━━━ 32s 299ms/step - accuracy: 0.9936 - loss: 0.0155 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9936 - loss: 0.0155 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9937 - loss: 0.0154 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  15/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9937 - loss: 0.0153 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  16/120 ━━━━━━━━━━━━━━━━━━━━ 31s 299ms/step - accuracy: 0.9937 - loss: 0.0153 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9937 - loss: 0.0152 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9938 - loss: 0.0152 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  19/120 ━━━━━━━━━━━━━━━━━━━━ 30s 299ms/step - accuracy: 0.9938 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9938 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9938 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  22/120 ━━━━━━━━━━━━━━━━━━━━ 29s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  26/120 ━━━━━━━━━━━━━━━━━━━━ 28s 299ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  29/120 ━━━━━━━━━━━━━━━━━━━━ 27s 299ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  32/120 ━━━━━━━━━━━━━━━━━━━━ 26s 299ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9940 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  36/120 ━━━━━━━━━━━━━━━━━━━━ 25s 299ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 299ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  39/120 ━━━━━━━━━━━━━━━━━━━━ 24s 298ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9941 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 298ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  46/120 ━━━━━━━━━━━━━━━━━━━━ 22s 298ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9942 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9942 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 298ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 298ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 299ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  56/120 ━━━━━━━━━━━━━━━━━━━━ 19s 298ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9943 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9943 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 298ms/step - accuracy: 0.9943 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9944 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9944 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 298ms/step - accuracy: 0.9944 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 298ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 298ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 298ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9946 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 - val_accuracy: 0.9757 - val_loss: 0.1176 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4946 Epoch 23/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 295ms/step - accuracy: 0.9930 - loss: 0.0170 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9929 - loss: 0.0173 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9929 - loss: 0.0172 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4942  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9931 - loss: 0.0168 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4943  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9933 - loss: 0.0164 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4944  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9934 - loss: 0.0162 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4945  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9935 - loss: 0.0159 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9936 - loss: 0.0157 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4946  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9937 - loss: 0.0155 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 292ms/step - accuracy: 0.9937 - loss: 0.0154 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4947  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9938 - loss: 0.0153 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 292ms/step - accuracy: 0.9938 - loss: 0.0152 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9938 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4948  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9939 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9939 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9939 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 293ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4949  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9940 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9940 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9941 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9942 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9943 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9944 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9944 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9944 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 296ms/step - accuracy: 0.9944 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9945 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9946 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9946 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9946 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9946 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9946 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9946 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 297ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 297ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9946 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9946 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9946 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9946 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9947 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9947 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9947 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9947 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9947 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9947 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9947 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9948 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9948 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9948 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9948 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9948 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9948 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9948 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9950 - loss: 0.0124 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 - val_accuracy: 0.9755 - val_loss: 0.1327 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4958 Epoch 24/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9949 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 292ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  4/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 292ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 293ms/step - accuracy: 0.9949 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  11/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  18/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 294ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9949 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9949 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 294ms/step - accuracy: 0.9949 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  25/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9949 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9949 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9949 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 294ms/step - accuracy: 0.9948 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 294ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 294ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960  35/120 ━━━━━━━━━━━━━━━━━━━━ 24s 294ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  42/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  45/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 293ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  49/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  52/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  59/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 293ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  66/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  69/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  76/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 294ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 294ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 295ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 295ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  93/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 295ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 296ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 300ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 - val_accuracy: 0.9755 - val_loss: 0.1223 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4950 Epoch 25/25  1/120 ━━━━━━━━━━━━━━━━━━━━ 35s 296ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  2/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9938 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  3/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9937 - loss: 0.0153 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4950  4/120 ━━━━━━━━━━━━━━━━━━━━ 34s 293ms/step - accuracy: 0.9938 - loss: 0.0151 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4951  5/120 ━━━━━━━━━━━━━━━━━━━━ 33s 294ms/step - accuracy: 0.9938 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  6/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9938 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  7/120 ━━━━━━━━━━━━━━━━━━━━ 33s 295ms/step - accuracy: 0.9938 - loss: 0.0150 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4952  8/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9939 - loss: 0.0149 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  9/120 ━━━━━━━━━━━━━━━━━━━━ 32s 294ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  10/120 ━━━━━━━━━━━━━━━━━━━━ 32s 293ms/step - accuracy: 0.9939 - loss: 0.0148 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4953  11/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9939 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  12/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  13/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  14/120 ━━━━━━━━━━━━━━━━━━━━ 31s 293ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  15/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  16/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  17/120 ━━━━━━━━━━━━━━━━━━━━ 30s 294ms/step - accuracy: 0.9940 - loss: 0.0147 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  18/120 ━━━━━━━━━━━━━━━━━━━━ 30s 295ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  19/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  20/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  21/120 ━━━━━━━━━━━━━━━━━━━━ 29s 295ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  22/120 ━━━━━━━━━━━━━━━━━━━━ 28s 295ms/step - accuracy: 0.9940 - loss: 0.0146 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  23/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9940 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4954  24/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  25/120 ━━━━━━━━━━━━━━━━━━━━ 28s 296ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  26/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9941 - loss: 0.0145 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  27/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  28/120 ━━━━━━━━━━━━━━━━━━━━ 27s 296ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  29/120 ━━━━━━━━━━━━━━━━━━━━ 26s 296ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  30/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9941 - loss: 0.0144 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  31/120 ━━━━━━━━━━━━━━━━━━━━ 26s 295ms/step - accuracy: 0.9941 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  32/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  33/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  34/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9942 - loss: 0.0143 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  35/120 ━━━━━━━━━━━━━━━━━━━━ 25s 295ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  36/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  37/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9942 - loss: 0.0142 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  38/120 ━━━━━━━━━━━━━━━━━━━━ 24s 295ms/step - accuracy: 0.9942 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  39/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9942 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  40/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9943 - loss: 0.0141 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  41/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4955  42/120 ━━━━━━━━━━━━━━━━━━━━ 23s 295ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  43/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  44/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9943 - loss: 0.0140 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  45/120 ━━━━━━━━━━━━━━━━━━━━ 22s 296ms/step - accuracy: 0.9943 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  46/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9943 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  47/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9944 - loss: 0.0139 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  48/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  49/120 ━━━━━━━━━━━━━━━━━━━━ 21s 296ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  50/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9944 - loss: 0.0138 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  51/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  52/120 ━━━━━━━━━━━━━━━━━━━━ 20s 296ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  53/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9944 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  54/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9945 - loss: 0.0137 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  55/120 ━━━━━━━━━━━━━━━━━━━━ 19s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4956  56/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  57/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9945 - loss: 0.0136 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  58/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  59/120 ━━━━━━━━━━━━━━━━━━━━ 18s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  60/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  61/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9945 - loss: 0.0135 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  62/120 ━━━━━━━━━━━━━━━━━━━━ 17s 296ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  63/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  64/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9946 - loss: 0.0134 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  65/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9946 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  66/120 ━━━━━━━━━━━━━━━━━━━━ 16s 296ms/step - accuracy: 0.9946 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  67/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9946 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  68/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9946 - loss: 0.0133 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  69/120 ━━━━━━━━━━━━━━━━━━━━ 15s 296ms/step - accuracy: 0.9946 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4957  70/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9946 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  71/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  72/120 ━━━━━━━━━━━━━━━━━━━━ 14s 297ms/step - accuracy: 0.9947 - loss: 0.0132 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  73/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  74/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  75/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  76/120 ━━━━━━━━━━━━━━━━━━━━ 13s 297ms/step - accuracy: 0.9947 - loss: 0.0131 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  77/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  78/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  79/120 ━━━━━━━━━━━━━━━━━━━━ 12s 297ms/step - accuracy: 0.9947 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  80/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  81/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9948 - loss: 0.0130 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  82/120 ━━━━━━━━━━━━━━━━━━━━ 11s 297ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  83/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  84/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  85/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9948 - loss: 0.0129 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4958  86/120 ━━━━━━━━━━━━━━━━━━━━ 10s 297ms/step - accuracy: 0.9948 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  87/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9948 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959   88/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9948 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  89/120 ━━━━━━━━━━━━━━━━━━━━ 9s 297ms/step - accuracy: 0.9948 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  90/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9948 - loss: 0.0128 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  91/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  92/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  93/120 ━━━━━━━━━━━━━━━━━━━━ 8s 297ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  94/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  95/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  96/120 ━━━━━━━━━━━━━━━━━━━━ 7s 297ms/step - accuracy: 0.9949 - loss: 0.0127 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  97/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  98/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959  99/120 ━━━━━━━━━━━━━━━━━━━━ 6s 297ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 100/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 101/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 102/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9949 - loss: 0.0126 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 103/120 ━━━━━━━━━━━━━━━━━━━━ 5s 297ms/step - accuracy: 0.9949 - loss: 0.0125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 104/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9950 - loss: 0.0125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 105/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9950 - loss: 0.0125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4959 106/120 ━━━━━━━━━━━━━━━━━━━━ 4s 297ms/step - accuracy: 0.9950 - loss: 0.0125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 107/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9950 - loss: 0.0125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 108/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9950 - loss: 0.0125 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 109/120 ━━━━━━━━━━━━━━━━━━━━ 3s 297ms/step - accuracy: 0.9950 - loss: 0.0124 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 110/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9950 - loss: 0.0124 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 111/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9950 - loss: 0.0124 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 112/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9950 - loss: 0.0124 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 113/120 ━━━━━━━━━━━━━━━━━━━━ 2s 297ms/step - accuracy: 0.9950 - loss: 0.0124 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 114/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9950 - loss: 0.0124 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 115/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9950 - loss: 0.0124 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 116/120 ━━━━━━━━━━━━━━━━━━━━ 1s 297ms/step - accuracy: 0.9950 - loss: 0.0123 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 117/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9950 - loss: 0.0123 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 118/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9950 - loss: 0.0123 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 119/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9950 - loss: 0.0123 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 120/120 ━━━━━━━━━━━━━━━━━━━━ 0s 297ms/step - accuracy: 0.9951 - loss: 0.0123 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4960 120/120 ━━━━━━━━━━━━━━━━━━━━ 36s 301ms/step - accuracy: 0.9958 - loss: 0.0106 - mean_absolute_error: 0.5000 - mean_squared_error: 0.4965 - val_accuracy: 0.9758 - val_loss: 0.1317 - val_mean_absolute_error: 0.5000 - val_mean_squared_error: 0.4958 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 478ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 488ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 45ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 54ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 57ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 66ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 45ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 65ms/step 1/1 ━━━━━━━━━━━━━━━━━━━━ 0s 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