Epoch 1/10
    Mini-Batch: 0 - Train Loss: 3.6975650787353516  - Test Loss: 2.2600717544555664

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118/118 [==============================] - ETA: 0s - loss: 3.0611 - accuracy: 0.2171
118/118 [==============================] - 222s 2s/step - loss: 3.0776 - accuracy: 0.2033 - val_loss: 3.0776 - val_accuracy: 0.2033
Epoch 2/10
    Mini-Batch: 0 - Train Loss: 0.05986182391643524  - Test Loss: 3.0712451934814453

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118/118 [==============================] - ETA: 0s - loss: 3.8049 - accuracy: 0.2172
118/118 [==============================] - 232s 2s/step - loss: 3.8404 - accuracy: 0.2077 - val_loss: 3.8404 - val_accuracy: 0.2077
Epoch 3/10
    Mini-Batch: 0 - Train Loss: 0.04529648274183273  - Test Loss: 3.8285374641418457

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118/118 [==============================] - ETA: 0s - loss: 2.4252 - accuracy: 0.3888
118/118 [==============================] - 234s 2s/step - loss: 2.5249 - accuracy: 0.3766 - val_loss: 2.5249 - val_accuracy: 0.3766
Epoch 4/10
    Mini-Batch: 0 - Train Loss: 0.02159746363759041  - Test Loss: 2.5887207984924316

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118/118 [==============================] - ETA: 0s - loss: 0.5095 - accuracy: 0.8286
118/118 [==============================] - 230s 2s/step - loss: 0.4836 - accuracy: 0.8265 - val_loss: 0.4836 - val_accuracy: 0.8265
Epoch 5/10
    Mini-Batch: 0 - Train Loss: 0.040719859302043915  - Test Loss: 0.5705890655517578

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118/118 [==============================] - ETA: 0s - loss: 0.0672 - accuracy: 0.9783
118/118 [==============================] - 241s 2s/step - loss: 0.0602 - accuracy: 0.9806 - val_loss: 0.0602 - val_accuracy: 0.9806
Epoch 6/10
    Mini-Batch: 0 - Train Loss: 0.01284988597035408  - Test Loss: 0.06039871275424957

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116/118 [============================>.] - ETA: 4s - loss: 0.0395 - accuracy: 0.9868    Mini-Batch: 116 - Train Loss: 0.03850457817316055  - Test Loss: 0.04035574197769165

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118/118 [==============================] - ETA: 0s - loss: 0.0400 - accuracy: 0.9867
118/118 [==============================] - 257s 2s/step - loss: 0.0391 - accuracy: 0.9868 - val_loss: 0.0391 - val_accuracy: 0.9868
Epoch 7/10
    Mini-Batch: 0 - Train Loss: 0.004964002408087254  - Test Loss: 0.039119210094213486

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103/118 [=========================>....] - ETA: 59s - loss: 0.0306 - accuracy: 0.9904     Mini-Batch: 103 - Train Loss: 0.03128152713179588  - Test Loss: 0.03589435666799545

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115/118 [============================>.] - ETA: 12s - loss: 0.0474 - accuracy: 0.9852    Mini-Batch: 115 - Train Loss: 0.05181689187884331  - Test Loss: 0.055232226848602295

116/118 [============================>.] - ETA: 8s - loss: 0.0518 - accuracy: 0.9846     Mini-Batch: 116 - Train Loss: 0.05323243513703346  - Test Loss: 0.04600515961647034

117/118 [============================>.] - ETA: 4s - loss: 0.0532 - accuracy: 0.9844    Mini-Batch: 117 - Train Loss: 0.04558838903903961  - Test Loss: 0.04025718569755554

118/118 [==============================] - ETA: 0s - loss: 0.0456 - accuracy: 0.9856
118/118 [==============================] - 478s 4s/step - loss: 0.0403 - accuracy: 0.9872 - val_loss: 0.0403 - val_accuracy: 0.9872
Epoch 8/10
    Mini-Batch: 0 - Train Loss: 0.002262404654175043  - Test Loss: 0.03629984334111214

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111/118 [===========================>..] - ETA: 32s - loss: 0.0326 - accuracy: 0.9898    Mini-Batch: 111 - Train Loss: 0.032910894602537155  - Test Loss: 0.036092814058065414

112/118 [===========================>..] - ETA: 27s - loss: 0.0329 - accuracy: 0.9896    Mini-Batch: 112 - Train Loss: 0.034589339047670364  - Test Loss: 0.038226157426834106

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115/118 [============================>.] - ETA: 13s - loss: 0.0386 - accuracy: 0.9882    Mini-Batch: 115 - Train Loss: 0.03852606192231178  - Test Loss: 0.039041511714458466

116/118 [============================>.] - ETA: 9s - loss: 0.0385 - accuracy: 0.9880     Mini-Batch: 116 - Train Loss: 0.03739643096923828  - Test Loss: 0.03673989325761795

117/118 [============================>.] - ETA: 4s - loss: 0.0374 - accuracy: 0.9884    Mini-Batch: 117 - Train Loss: 0.03651045262813568  - Test Loss: 0.03313565254211426

118/118 [==============================] - ETA: 0s - loss: 0.0365 - accuracy: 0.9888
118/118 [==============================] - 540s 5s/step - loss: 0.0331 - accuracy: 0.9900 - val_loss: 0.0331 - val_accuracy: 0.9900
Epoch 9/10
    Mini-Batch: 0 - Train Loss: 0.002615374280139804  - Test Loss: 0.03379034250974655

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105/118 [=========================>....] - ETA: 59s - loss: 0.0296 - accuracy: 0.9910     Mini-Batch: 105 - Train Loss: 0.02974768355488777  - Test Loss: 0.031763654202222824

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113/118 [===========================>..] - ETA: 22s - loss: 0.0312 - accuracy: 0.9904    Mini-Batch: 113 - Train Loss: 0.031016036868095398  - Test Loss: 0.03205506131052971

114/118 [===========================>..] - ETA: 18s - loss: 0.0310 - accuracy: 0.9904    Mini-Batch: 114 - Train Loss: 0.030570141971111298  - Test Loss: 0.031818684190511703

115/118 [============================>.] - ETA: 13s - loss: 0.0306 - accuracy: 0.9906    Mini-Batch: 115 - Train Loss: 0.030407140031456947  - Test Loss: 0.03163360804319382

116/118 [============================>.] - ETA: 9s - loss: 0.0304 - accuracy: 0.9907     Mini-Batch: 116 - Train Loss: 0.03042430989444256  - Test Loss: 0.03121112659573555

117/118 [============================>.] - ETA: 4s - loss: 0.0304 - accuracy: 0.9907    Mini-Batch: 117 - Train Loss: 0.030918247997760773  - Test Loss: 0.030985461547970772

118/118 [==============================] - ETA: 0s - loss: 0.0309 - accuracy: 0.9908
118/118 [==============================] - 539s 5s/step - loss: 0.0310 - accuracy: 0.9909 - val_loss: 0.0310 - val_accuracy: 0.9909
Epoch 10/10
    Mini-Batch: 0 - Train Loss: 0.0024309661239385605  - Test Loss: 0.03067745268344879

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115/118 [============================>.] - ETA: 13s - loss: 0.0339 - accuracy: 0.9902    Mini-Batch: 115 - Train Loss: 0.0346270389854908  - Test Loss: 0.03729020431637764

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117/118 [============================>.] - ETA: 4s - loss: 0.0356 - accuracy: 0.9896    Mini-Batch: 117 - Train Loss: 0.03771735355257988  - Test Loss: 0.03912104666233063

118/118 [==============================] - ETA: 0s - loss: 0.0377 - accuracy: 0.9890
118/118 [==============================] - 549s 5s/step - loss: 0.0391 - accuracy: 0.9886 - val_loss: 0.0391 - val_accuracy: 0.9886
1875/1875 - 27s - loss: 0.0023 - accuracy: 0.9998 - 27s/epoch - 14ms/step
313/313 - 4s - loss: 0.0391 - accuracy: 0.9886 - 4s/epoch - 14ms/step
Train loss: 0.002271930454298854
Train accuracy: 0.9998499751091003
Test loss: 0.03912104666233063
Test accuracy: 0.9886000156402588

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313/313 [==============================] - 5s 15ms/step
              precision    recall  f1-score   support

           0  0.9809045226 0.9959183673 0.9883544304       980
           1  0.9869565217 1.0000000000 0.9934354486      1135
           2  0.9827089337 0.9912790698 0.9869753980      1032
           3  0.9901283317 0.9930693069 0.9915966387      1010
           4  0.9908536585 0.9928716904 0.9918616480       982
           5  0.9855072464 0.9910313901 0.9882615987       892
           6  0.9989293362 0.9739039666 0.9862579281       958
           7  0.9864472410 0.9912451362 0.9888403688      1028
           8  0.9917012448 0.9815195072 0.9865841073       974
           9  0.9929221436 0.9732408325 0.9829829830      1009

    accuracy                      0.9886000000     10000
   macro avg  0.9887059180 0.9884079267 0.9885150549     10000
weighted avg  0.9886575599 0.9886000000 0.9885871021     10000