학습 중 validation loss와 validation accuracy가 급격하게 변하는 현상의 원인은 무엇일까요?

강사님 F/B 고맙습니다. 먼저 관련 내용 업데이트하여 드리면 0. Class 수 : 10개입니다만, 각 Class 별로 데이터의 수가 좀 많이 차이가 납니다(현장에서 구할 수 있는 데이터 종류가 한정되어 그렇습니다). (사진) 1. 라벨링 재확인 : 유사한 현상이 있는 점은 어쩔 수가 없고, 완전히 잘못된 분류는 없는 관계로 그대로 진행하였습니다. 2. 모델의 재학습 : 라벨링에 변화가 없어서 효과가 그닥 없었습니다. 3. 추가 검증 : 배치 크기 변경 이후에 나머지 수업을 들으면서 모델을 조금 변경해보았습니다. 3.1 적용 사항 : 'Callback을 통한 동적 학습율 변경', 'MaxPooling 대신 각 세트의 마지막 Conv2D에 stride=2 적용' (아래에 코드 올려드립니다. third feature extractor에는 채널을 2배로 늘린 Conv2D 층을 추가하고 여기에 stride=2를 적용하였습니다) (사진) 3.2 적용 결과 : Batch size 2, 4, 8, 16, 32로 학습 실시 (학습 history는 맨아래 첨부하였습니다) (사진) 3.3 결론 : Batch size가 클수록 학습 중반까지 val_loss와 val_accuracy가 튀는 현상이 있지만 확실히 정돈된 모습이고, epoch가 20을 넘어가면 사라지는 걸로 봐서는 어느 정도 해결된 것으로 보입니다. 다만 변경 사항이 많아 어떤 것이 직접적으로 처음의 현상을 유발하였는지는 파악되지 않았습니다(구글링 해봐도 라벨링이 맞다면 학습율을 조정해보라는 답변이 대부분있습니다). 다음에 시간을 좀 내어 무엇이 원인인지 차근차근 분석을 해보려고 합니다. 좋은 강의 언제나 고맙습니다. Found 2198 files belonging to 10 classes. Using 1979 files for training. Found 2198 files belonging to 10 classes. Using 219 files for validation. Epoch 1/30 990/990 [==============================] - 45s 45ms/step - loss: 3.7603 - accuracy: 0.4687 - val_loss: 1.3357 - val_accuracy: 0.7991 Epoch 2/30 990/990 [==============================] - 42s 43ms/step - loss: 2.0769 - accuracy: 0.7721 - val_loss: 0.9707 - val_accuracy: 0.8219 Epoch 3/30 990/990 [==============================] - 43s 43ms/step - loss: 1.0833 - accuracy: 0.8606 - val_loss: 3.2453 - val_accuracy: 0.8311 Epoch 4/30 990/990 [==============================] - 42s 43ms/step - loss: 1.6504 - accuracy: 0.8544 - val_loss: 1.9043 - val_accuracy: 0.8858 Epoch 5/30 990/990 [==============================] - 43s 44ms/step - loss: 1.0653 - accuracy: 0.8989 - val_loss: 1.9502 - val_accuracy: 0.9132 Epoch 6/30 990/990 [==============================] - 44s 44ms/step - loss: 1.4879 - accuracy: 0.8866 - val_loss: 3.1987 - val_accuracy: 0.8995 Epoch 7/30 990/990 [==============================] - 43s 44ms/step - loss: 1.3159 - accuracy: 0.9005 - val_loss: 6.7991 - val_accuracy: 0.8767 Epoch 00007: ReduceLROnPlateau reducing learning rate to 1.9999999494757503e-05. Epoch 8/30 990/990 [==============================] - 43s 43ms/step - loss: 0.3560 - accuracy: 0.9632 - val_loss: 1.9258 - val_accuracy: 0.9315 Epoch 9/30 990/990 [==============================] - 42s 43ms/step - loss: 0.3567 - accuracy: 0.9725 - val_loss: 1.7539 - val_accuracy: 0.9361 Epoch 10/30 990/990 [==============================] - 43s 44ms/step - loss: 0.2482 - accuracy: 0.9761 - val_loss: 1.6857 - val_accuracy: 0.9498 Epoch 11/30 990/990 [==============================] - 43s 44ms/step - loss: 0.3200 - accuracy: 0.9772 - val_loss: 0.7950 - val_accuracy: 0.9635 Epoch 12/30 990/990 [==============================] - 43s 44ms/step - loss: 0.4093 - accuracy: 0.9615 - val_loss: 1.2214 - val_accuracy: 0.9498 Epoch 13/30 990/990 [==============================] - 43s 43ms/step - loss: 0.1854 - accuracy: 0.9814 - val_loss: 2.9158 - val_accuracy: 0.9269 Epoch 14/30 990/990 [==============================] - 43s 44ms/step - loss: 0.2508 - accuracy: 0.9735 - val_loss: 2.2683 - val_accuracy: 0.9543 Epoch 15/30 990/990 [==============================] - 43s 43ms/step - loss: 0.1775 - accuracy: 0.9836 - val_loss: 1.6626 - val_accuracy: 0.9543 Epoch 16/30 990/990 [==============================] - 43s 44ms/step - loss: 0.1664 - accuracy: 0.9740 - val_loss: 2.1867 - val_accuracy: 0.9498 Epoch 00016: ReduceLROnPlateau reducing learning rate to 3.999999898951501e-06. Epoch 17/30 990/990 [==============================] - 43s 44ms/step - loss: 0.1387 - accuracy: 0.9795 - val_loss: 2.0234 - val_accuracy: 0.9589 Epoch 18/30 990/990 [==============================] - 43s 44ms/step - loss: 0.1506 - accuracy: 0.9799 - val_loss: 1.7870 - val_accuracy: 0.9498 Epoch 19/30 990/990 [==============================] - 43s 43ms/step - loss: 0.2060 - accuracy: 0.9843 - val_loss: 2.2668 - val_accuracy: 0.9589 Epoch 20/30 990/990 [==============================] - 43s 43ms/step - loss: 0.0962 - accuracy: 0.9895 - val_loss: 1.9903 - val_accuracy: 0.9543 Epoch 21/30 990/990 [==============================] - 43s 43ms/step - loss: 0.1770 - accuracy: 0.9870 - val_loss: 2.3954 - val_accuracy: 0.9543 Epoch 00021: ReduceLROnPlateau reducing learning rate to 7.999999979801942e-07. Epoch 22/30 990/990 [==============================] - 43s 43ms/step - loss: 0.0832 - accuracy: 0.9818 - val_loss: 2.1405 - val_accuracy: 0.9543 Epoch 23/30 990/990 [==============================] - 44s 44ms/step - loss: 0.0871 - accuracy: 0.9855 - val_loss: 2.2400 - val_accuracy: 0.9543 Epoch 24/30 990/990 [==============================] - 43s 44ms/step - loss: 0.1387 - accuracy: 0.9799 - val_loss: 2.2669 - val_accuracy: 0.9498 Epoch 25/30 990/990 [==============================] - 43s 44ms/step - loss: 0.1580 - accuracy: 0.9879 - val_loss: 2.2107 - val_accuracy: 0.9498 Epoch 26/30 990/990 [==============================] - 44s 44ms/step - loss: 0.1013 - accuracy: 0.9866 - val_loss: 2.1473 - val_accuracy: 0.9543 Epoch 00026: ReduceLROnPlateau reducing learning rate to 1.600000018697756e-07. Epoch 27/30 990/990 [==============================] - 43s 43ms/step - loss: 0.1389 - accuracy: 0.9832 - val_loss: 2.1720 - val_accuracy: 0.9543 Epoch 28/30 990/990 [==============================] - 43s 44ms/step - loss: 0.1184 - accuracy: 0.9838 - val_loss: 2.1016 - val_accuracy: 0.9543 Epoch 29/30 990/990 [==============================] - 43s 43ms/step - loss: 0.1844 - accuracy: 0.9788 - val_loss: 2.0670 - val_accuracy: 0.9543 Epoch 30/30 990/990 [==============================] - 44s 44ms/step - loss: 0.0829 - accuracy: 0.9887 - val_loss: 2.0866 - val_accuracy: 0.9543 110/110 [==============================] - 1s 9ms/step - loss: 2.0866 - accuracy: 0.9543 Found 2198 files belonging to 10 classes. Using 1979 files for training. Found 2198 files belonging to 10 classes. Using 219 files for validation. Epoch 1/30 495/495 [==============================] - 33s 66ms/step - loss: 2.5201 - accuracy: 0.4496 - val_loss: 0.4513 - val_accuracy: 0.8493 Epoch 2/30 495/495 [==============================] - 32s 65ms/step - loss: 1.2881 - accuracy: 0.7432 - val_loss: 1.0306 - val_accuracy: 0.7489 Epoch 3/30 495/495 [==============================] - 33s 66ms/step - loss: 1.1680 - accuracy: 0.8176 - val_loss: 1.1881 - val_accuracy: 0.9087 Epoch 4/30 495/495 [==============================] - 33s 66ms/step - loss: 1.1353 - accuracy: 0.8447 - val_loss: 12.3741 - val_accuracy: 0.4292 Epoch 5/30 495/495 [==============================] - 32s 65ms/step - loss: 1.0116 - accuracy: 0.8637 - val_loss: 30.4661 - val_accuracy: 0.3653 Epoch 6/30 495/495 [==============================] - 33s 66ms/step - loss: 1.1948 - accuracy: 0.8802 - val_loss: 3.0824 - val_accuracy: 0.7763 Epoch 00006: ReduceLROnPlateau reducing learning rate to 1.9999999494757503e-05. Epoch 7/30 495/495 [==============================] - 33s 66ms/step - loss: 0.9830 - accuracy: 0.9211 - val_loss: 0.6620 - val_accuracy: 0.9635 Epoch 8/30 495/495 [==============================] - 33s 67ms/step - loss: 0.7374 - accuracy: 0.9316 - val_loss: 0.6927 - val_accuracy: 0.9726 Epoch 9/30 495/495 [==============================] - 33s 67ms/step - loss: 0.7204 - accuracy: 0.9381 - val_loss: 0.5492 - val_accuracy: 0.9589 Epoch 10/30 495/495 [==============================] - 33s 67ms/step - loss: 0.8152 - accuracy: 0.9333 - val_loss: 0.5120 - val_accuracy: 0.9680 Epoch 11/30 495/495 [==============================] - 33s 66ms/step - loss: 0.6594 - accuracy: 0.9445 - val_loss: 0.4779 - val_accuracy: 0.9817 Epoch 00011: ReduceLROnPlateau reducing learning rate to 3.999999898951501e-06. Epoch 12/30 495/495 [==============================] - 34s 68ms/step - loss: 0.5233 - accuracy: 0.9489 - val_loss: 0.5502 - val_accuracy: 0.9772 Epoch 13/30 495/495 [==============================] - 33s 67ms/step - loss: 0.5145 - accuracy: 0.9498 - val_loss: 0.4927 - val_accuracy: 0.9772 Epoch 14/30 495/495 [==============================] - 33s 67ms/step - loss: 0.6242 - accuracy: 0.9497 - val_loss: 0.3954 - val_accuracy: 0.9772 Epoch 15/30 495/495 [==============================] - 33s 66ms/step - loss: 0.5388 - accuracy: 0.9490 - val_loss: 0.4569 - val_accuracy: 0.9726 Epoch 16/30 495/495 [==============================] - 33s 67ms/step - loss: 0.5238 - accuracy: 0.9505 - val_loss: 0.3898 - val_accuracy: 0.9772 Epoch 17/30 495/495 [==============================] - 34s 68ms/step - loss: 0.3283 - accuracy: 0.9607 - val_loss: 0.3942 - val_accuracy: 0.9817 Epoch 18/30 495/495 [==============================] - 33s 67ms/step - loss: 0.3745 - accuracy: 0.9521 - val_loss: 0.4565 - val_accuracy: 0.9772 Epoch 19/30 495/495 [==============================] - 34s 68ms/step - loss: 0.3927 - accuracy: 0.9558 - val_loss: 0.4310 - val_accuracy: 0.9726 Epoch 20/30 495/495 [==============================] - 34s 68ms/step - loss: 0.4973 - accuracy: 0.9547 - val_loss: 0.4792 - val_accuracy: 0.9726 Epoch 21/30 495/495 [==============================] - 33s 67ms/step - loss: 0.5840 - accuracy: 0.9521 - val_loss: 0.3660 - val_accuracy: 0.9726 Epoch 22/30 495/495 [==============================] - 33s 68ms/step - loss: 0.4568 - accuracy: 0.9572 - val_loss: 0.4898 - val_accuracy: 0.9680 Epoch 23/30 495/495 [==============================] - 33s 66ms/step - loss: 0.4546 - accuracy: 0.9548 - val_loss: 0.3170 - val_accuracy: 0.9772 Epoch 24/30 495/495 [==============================] - 33s 67ms/step - loss: 0.4663 - accuracy: 0.9669 - val_loss: 0.3242 - val_accuracy: 0.9772 Epoch 25/30 495/495 [==============================] - 34s 68ms/step - loss: 0.3522 - accuracy: 0.9667 - val_loss: 0.2901 - val_accuracy: 0.9772 Epoch 26/30 495/495 [==============================] - 34s 68ms/step - loss: 0.3148 - accuracy: 0.9622 - val_loss: 0.2605 - val_accuracy: 0.9772 Epoch 27/30 495/495 [==============================] - 33s 67ms/step - loss: 0.3931 - accuracy: 0.9629 - val_loss: 0.2825 - val_accuracy: 0.9772 Epoch 28/30 495/495 [==============================] - 36s 73ms/step - loss: 0.2411 - accuracy: 0.9763 - val_loss: 0.3732 - val_accuracy: 0.9772 Epoch 29/30 495/495 [==============================] - 36s 72ms/step - loss: 0.3437 - accuracy: 0.9626 - val_loss: 0.2420 - val_accuracy: 0.9772 Epoch 30/30 495/495 [==============================] - 37s 74ms/step - loss: 0.2893 - accuracy: 0.9572 - val_loss: 0.3341 - val_accuracy: 0.9726 55/55 [==============================] - 1s 17ms/step - loss: 0.3341 - accuracy: 0.9726 Found 2198 files belonging to 10 classes. Using 1979 files for training. Found 2198 files belonging to 10 classes. Using 219 files for validation. Epoch 1/30 248/248 [==============================] - 34s 134ms/step - loss: 2.4453 - accuracy: 0.4738 - val_loss: 1.3434 - val_accuracy: 0.5023 Epoch 2/30 248/248 [==============================] - 33s 133ms/step - loss: 1.0834 - accuracy: 0.7897 - val_loss: 0.8532 - val_accuracy: 0.8721 Epoch 3/30 248/248 [==============================] - 33s 133ms/step - loss: 0.8777 - accuracy: 0.8544 - val_loss: 0.3363 - val_accuracy: 0.8904 Epoch 4/30 248/248 [==============================] - 34s 136ms/step - loss: 0.4220 - accuracy: 0.9184 - val_loss: 1.9280 - val_accuracy: 0.7534 Epoch 5/30 248/248 [==============================] - 34s 136ms/step - loss: 0.8649 - accuracy: 0.8911 - val_loss: 10.5595 - val_accuracy: 0.4749 Epoch 6/30 248/248 [==============================] - 34s 136ms/step - loss: 0.6193 - accuracy: 0.9305 - val_loss: 2.4152 - val_accuracy: 0.7260 Epoch 7/30 248/248 [==============================] - 34s 136ms/step - loss: 0.5930 - accuracy: 0.9232 - val_loss: 7.2804 - val_accuracy: 0.5708 Epoch 8/30 248/248 [==============================] - 32s 131ms/step - loss: 0.5178 - accuracy: 0.9380 - val_loss: 0.8919 - val_accuracy: 0.8767 Epoch 00008: ReduceLROnPlateau reducing learning rate to 1.9999999494757503e-05. Epoch 9/30 248/248 [==============================] - 31s 125ms/step - loss: 0.4003 - accuracy: 0.9527 - val_loss: 0.3027 - val_accuracy: 0.9680 Epoch 10/30 248/248 [==============================] - 31s 126ms/step - loss: 0.2557 - accuracy: 0.9681 - val_loss: 0.5277 - val_accuracy: 0.9178 Epoch 11/30 248/248 [==============================] - 31s 125ms/step - loss: 0.1611 - accuracy: 0.9723 - val_loss: 0.1921 - val_accuracy: 0.9817 Epoch 12/30 248/248 [==============================] - 31s 124ms/step - loss: 0.1882 - accuracy: 0.9744 - val_loss: 0.1635 - val_accuracy: 0.9726 Epoch 13/30 248/248 [==============================] - 31s 125ms/step - loss: 0.2039 - accuracy: 0.9722 - val_loss: 0.1953 - val_accuracy: 0.9772 Epoch 14/30 248/248 [==============================] - 33s 133ms/step - loss: 0.1774 - accuracy: 0.9687 - val_loss: 0.2438 - val_accuracy: 0.9589 Epoch 15/30 248/248 [==============================] - 32s 127ms/step - loss: 0.1543 - accuracy: 0.9776 - val_loss: 0.1310 - val_accuracy: 0.9817 Epoch 16/30 248/248 [==============================] - 31s 126ms/step - loss: 0.2269 - accuracy: 0.9720 - val_loss: 1.2158 - val_accuracy: 0.8584 Epoch 17/30 248/248 [==============================] - 32s 128ms/step - loss: 0.1476 - accuracy: 0.9771 - val_loss: 0.2541 - val_accuracy: 0.9772 Epoch 18/30 248/248 [==============================] - 33s 132ms/step - loss: 0.2217 - accuracy: 0.9710 - val_loss: 5.7592 - val_accuracy: 0.6941 Epoch 19/30 248/248 [==============================] - 32s 127ms/step - loss: 0.1599 - accuracy: 0.9754 - val_loss: 0.1691 - val_accuracy: 0.9726 Epoch 20/30 248/248 [==============================] - 32s 127ms/step - loss: 0.1280 - accuracy: 0.9781 - val_loss: 0.1678 - val_accuracy: 0.9817 Epoch 00020: ReduceLROnPlateau reducing learning rate to 3.999999898951501e-06. Epoch 21/30 248/248 [==============================] - 32s 129ms/step - loss: 0.1343 - accuracy: 0.9800 - val_loss: 0.0997 - val_accuracy: 0.9863 Epoch 22/30 248/248 [==============================] - 32s 127ms/step - loss: 0.1105 - accuracy: 0.9846 - val_loss: 0.1129 - val_accuracy: 0.9909 Epoch 23/30 248/248 [==============================] - 31s 126ms/step - loss: 0.0728 - accuracy: 0.9860 - val_loss: 0.1252 - val_accuracy: 0.9863 Epoch 24/30 248/248 [==============================] - 33s 132ms/step - loss: 0.1155 - accuracy: 0.9816 - val_loss: 0.1112 - val_accuracy: 0.9909 Epoch 25/30 248/248 [==============================] - 31s 126ms/step - loss: 0.1066 - accuracy: 0.9833 - val_loss: 0.1101 - val_accuracy: 0.9909 Epoch 26/30 248/248 [==============================] - 32s 129ms/step - loss: 0.0935 - accuracy: 0.9813 - val_loss: 0.1086 - val_accuracy: 0.9909 Epoch 00026: ReduceLROnPlateau reducing learning rate to 7.999999979801942e-07. Epoch 27/30 248/248 [==============================] - 33s 133ms/step - loss: 0.0873 - accuracy: 0.9864 - val_loss: 0.1137 - val_accuracy: 0.9909 Epoch 28/30 248/248 [==============================] - 32s 127ms/step - loss: 0.1407 - accuracy: 0.9810 - val_loss: 0.1155 - val_accuracy: 0.9909 Epoch 29/30 248/248 [==============================] - 32s 127ms/step - loss: 0.1072 - accuracy: 0.9866 - val_loss: 0.1150 - val_accuracy: 0.9909 Epoch 30/30 248/248 [==============================] - 31s 127ms/step - loss: 0.1200 - accuracy: 0.9796 - val_loss: 0.1157 - val_accuracy: 0.9954 28/28 [==============================] - 1s 38ms/step - loss: 0.1157 - accuracy: 0.9954 Found 2198 files belonging to 10 classes. Using 1979 files for training. Found 2198 files belonging to 10 classes. Using 219 files for validation. Epoch 1/30 124/124 [==============================] - 28s 218ms/step - loss: 2.1064 - accuracy: 0.4790 - val_loss: 3.8315 - val_accuracy: 0.1461 Epoch 2/30 124/124 [==============================] - 27s 215ms/step - loss: 0.8776 - accuracy: 0.7977 - val_loss: 0.6124 - val_accuracy: 0.8311 Epoch 3/30 124/124 [==============================] - 27s 218ms/step - loss: 0.6739 - accuracy: 0.8509 - val_loss: 1.6122 - val_accuracy: 0.7443 Epoch 4/30 124/124 [==============================] - 28s 222ms/step - loss: 0.5850 - accuracy: 0.8795 - val_loss: 1.1183 - val_accuracy: 0.7397 Epoch 5/30 124/124 [==============================] - 27s 220ms/step - loss: 0.4551 - accuracy: 0.9079 - val_loss: 0.4376 - val_accuracy: 0.9224 Epoch 6/30 124/124 [==============================] - 27s 216ms/step - loss: 0.5067 - accuracy: 0.9227 - val_loss: 0.3599 - val_accuracy: 0.9589 Epoch 7/30 124/124 [==============================] - 27s 219ms/step - loss: 0.5442 - accuracy: 0.9181 - val_loss: 1.0835 - val_accuracy: 0.8950 Epoch 8/30 124/124 [==============================] - 28s 222ms/step - loss: 0.4087 - accuracy: 0.9294 - val_loss: 4.1504 - val_accuracy: 0.6621 Epoch 9/30 124/124 [==============================] - 27s 218ms/step - loss: 0.2945 - accuracy: 0.9458 - val_loss: 2.0948 - val_accuracy: 0.8493 Epoch 10/30 124/124 [==============================] - 26s 213ms/step - loss: 0.4008 - accuracy: 0.9320 - val_loss: 0.6751 - val_accuracy: 0.9498 Epoch 11/30 124/124 [==============================] - 27s 215ms/step - loss: 0.2623 - accuracy: 0.9598 - val_loss: 2.6050 - val_accuracy: 0.7717 Epoch 00011: ReduceLROnPlateau reducing learning rate to 1.9999999494757503e-05. Epoch 12/30 124/124 [==============================] - 27s 218ms/step - loss: 0.2186 - accuracy: 0.9644 - val_loss: 0.4407 - val_accuracy: 0.9498 Epoch 13/30 124/124 [==============================] - 27s 214ms/step - loss: 0.1547 - accuracy: 0.9745 - val_loss: 0.1928 - val_accuracy: 0.9772 Epoch 14/30 124/124 [==============================] - 27s 216ms/step - loss: 0.1412 - accuracy: 0.9785 - val_loss: 0.1382 - val_accuracy: 0.9909 Epoch 15/30 124/124 [==============================] - 26s 213ms/step - loss: 0.0843 - accuracy: 0.9848 - val_loss: 0.2400 - val_accuracy: 0.9680 Epoch 16/30 124/124 [==============================] - 26s 210ms/step - loss: 0.0903 - accuracy: 0.9820 - val_loss: 0.1940 - val_accuracy: 0.9817 Epoch 17/30 124/124 [==============================] - 27s 214ms/step - loss: 0.0695 - accuracy: 0.9870 - val_loss: 0.1345 - val_accuracy: 0.9817 Epoch 18/30 124/124 [==============================] - 27s 217ms/step - loss: 0.0765 - accuracy: 0.9814 - val_loss: 0.1305 - val_accuracy: 0.9772 Epoch 19/30 124/124 [==============================] - 28s 222ms/step - loss: 0.0662 - accuracy: 0.9850 - val_loss: 0.1530 - val_accuracy: 0.9726 Epoch 20/30 124/124 [==============================] - 27s 215ms/step - loss: 0.0631 - accuracy: 0.9872 - val_loss: 0.2796 - val_accuracy: 0.9635 Epoch 21/30 124/124 [==============================] - 27s 214ms/step - loss: 0.0702 - accuracy: 0.9884 - val_loss: 0.1475 - val_accuracy: 0.9726 Epoch 22/30 124/124 [==============================] - 27s 214ms/step - loss: 0.0402 - accuracy: 0.9918 - val_loss: 0.0820 - val_accuracy: 0.9863 Epoch 23/30 124/124 [==============================] - 27s 215ms/step - loss: 0.0885 - accuracy: 0.9864 - val_loss: 0.3081 - val_accuracy: 0.9680 Epoch 24/30 124/124 [==============================] - 28s 223ms/step - loss: 0.0931 - accuracy: 0.9890 - val_loss: 0.3009 - val_accuracy: 0.9635 Epoch 25/30 124/124 [==============================] - 27s 218ms/step - loss: 0.0709 - accuracy: 0.9869 - val_loss: 0.2513 - val_accuracy: 0.9589 Epoch 26/30 124/124 [==============================] - 26s 213ms/step - loss: 0.0858 - accuracy: 0.9866 - val_loss: 0.2553 - val_accuracy: 0.9817 Epoch 27/30 124/124 [==============================] - 26s 210ms/step - loss: 0.0634 - accuracy: 0.9872 - val_loss: 0.2556 - val_accuracy: 0.9635 Epoch 00027: ReduceLROnPlateau reducing learning rate to 3.999999898951501e-06. Epoch 28/30 124/124 [==============================] - 26s 209ms/step - loss: 0.0677 - accuracy: 0.9895 - val_loss: 0.1815 - val_accuracy: 0.9772 Epoch 29/30 124/124 [==============================] - 26s 208ms/step - loss: 0.0476 - accuracy: 0.9841 - val_loss: 0.1988 - val_accuracy: 0.9817 Epoch 30/30 124/124 [==============================] - 26s 212ms/step - loss: 0.0292 - accuracy: 0.9941 - val_loss: 0.1808 - val_accuracy: 0.9817 14/14 [==============================] - 1s 62ms/step - loss: 0.1808 - accuracy: 0.9817 Found 2198 files belonging to 10 classes. Using 1979 files for training. Found 2198 files belonging to 10 classes. Using 219 files for validation. Epoch 1/30 62/62 [==============================] - 26s 412ms/step - loss: 2.2331 - accuracy: 0.4484 - val_loss: 5.4461 - val_accuracy: 0.1416 Epoch 2/30 62/62 [==============================] - 26s 412ms/step - loss: 0.7845 - accuracy: 0.7727 - val_loss: 4.0120 - val_accuracy: 0.1553 Epoch 3/30 62/62 [==============================] - 26s 410ms/step - loss: 0.6508 - accuracy: 0.8313 - val_loss: 1.5659 - val_accuracy: 0.2922 Epoch 4/30 62/62 [==============================] - 26s 411ms/step - loss: 0.4535 - accuracy: 0.8875 - val_loss: 0.5283 - val_accuracy: 0.8219 Epoch 5/30 62/62 [==============================] - 26s 411ms/step - loss: 0.4256 - accuracy: 0.9066 - val_loss: 0.3807 - val_accuracy: 0.8767 Epoch 6/30 62/62 [==============================] - 25s 410ms/step - loss: 0.5040 - accuracy: 0.9077 - val_loss: 4.2263 - val_accuracy: 0.4977 Epoch 7/30 62/62 [==============================] - 25s 407ms/step - loss: 0.2518 - accuracy: 0.9388 - val_loss: 0.4334 - val_accuracy: 0.9178 Epoch 8/30 62/62 [==============================] - 25s 402ms/step - loss: 0.2725 - accuracy: 0.9453 - val_loss: 1.2326 - val_accuracy: 0.8311 Epoch 9/30 62/62 [==============================] - 26s 416ms/step - loss: 0.3540 - accuracy: 0.9382 - val_loss: 1.1825 - val_accuracy: 0.7763 Epoch 10/30 62/62 [==============================] - 26s 425ms/step - loss: 0.1845 - accuracy: 0.9667 - val_loss: 0.3120 - val_accuracy: 0.9543 Epoch 11/30 62/62 [==============================] - 25s 408ms/step - loss: 0.1510 - accuracy: 0.9700 - val_loss: 3.5096 - val_accuracy: 0.6301 Epoch 12/30 62/62 [==============================] - 26s 414ms/step - loss: 0.2343 - accuracy: 0.9568 - val_loss: 0.2914 - val_accuracy: 0.9269 Epoch 13/30 62/62 [==============================] - 26s 412ms/step - loss: 0.1025 - accuracy: 0.9793 - val_loss: 0.4985 - val_accuracy: 0.9589 Epoch 14/30 62/62 [==============================] - 26s 420ms/step - loss: 0.0903 - accuracy: 0.9811 - val_loss: 6.7767 - val_accuracy: 0.5023 Epoch 15/30 62/62 [==============================] - 26s 411ms/step - loss: 0.1643 - accuracy: 0.9673 - val_loss: 0.1805 - val_accuracy: 0.9635 Epoch 16/30 62/62 [==============================] - 26s 418ms/step - loss: 0.1867 - accuracy: 0.9786 - val_loss: 0.2266 - val_accuracy: 0.9406 Epoch 17/30 62/62 [==============================] - 26s 418ms/step - loss: 0.3070 - accuracy: 0.9721 - val_loss: 0.2483 - val_accuracy: 0.9680 Epoch 18/30 62/62 [==============================] - 26s 410ms/step - loss: 0.1277 - accuracy: 0.9812 - val_loss: 1.1634 - val_accuracy: 0.8721 Epoch 19/30 62/62 [==============================] - 25s 409ms/step - loss: 0.1572 - accuracy: 0.9746 - val_loss: 0.2259 - val_accuracy: 0.9726 Epoch 20/30 62/62 [==============================] - 25s 407ms/step - loss: 0.1158 - accuracy: 0.9781 - val_loss: 8.5579 - val_accuracy: 0.6256 Epoch 00020: ReduceLROnPlateau reducing learning rate to 1.9999999494757503e-05. Epoch 21/30 62/62 [==============================] - 25s 410ms/step - loss: 0.1244 - accuracy: 0.9859 - val_loss: 0.2911 - val_accuracy: 0.9817 Epoch 22/30 62/62 [==============================] - 26s 417ms/step - loss: 0.0489 - accuracy: 0.9904 - val_loss: 0.2291 - val_accuracy: 0.9772 Epoch 23/30 62/62 [==============================] - 25s 407ms/step - loss: 0.0242 - accuracy: 0.9885 - val_loss: 0.1802 - val_accuracy: 0.9863 Epoch 24/30 62/62 [==============================] - 26s 416ms/step - loss: 0.0684 - accuracy: 0.9912 - val_loss: 0.1144 - val_accuracy: 0.9817 Epoch 25/30 62/62 [==============================] - 26s 418ms/step - loss: 0.0268 - accuracy: 0.9897 - val_loss: 0.1111 - val_accuracy: 0.9726 Epoch 26/30 62/62 [==============================] - 26s 418ms/step - loss: 0.0294 - accuracy: 0.9960 - val_loss: 0.1103 - val_accuracy: 0.9817 Epoch 27/30 62/62 [==============================] - 25s 407ms/step - loss: 0.0345 - accuracy: 0.9933 - val_loss: 0.1100 - val_accuracy: 0.9863 Epoch 28/30 62/62 [==============================] - 26s 416ms/step - loss: 0.0254 - accuracy: 0.9908 - val_loss: 0.1861 - val_accuracy: 0.9726 Epoch 29/30 62/62 [==============================] - 25s 408ms/step - loss: 0.0467 - accuracy: 0.9886 - val_loss: 0.1448 - val_accuracy: 0.9817 Epoch 30/30 62/62 [==============================] - 26s 415ms/step - loss: 0.0406 - accuracy: 0.9907 - val_loss: 0.1406 - val_accuracy: 0.9772 7/7 [==============================] - 1s 116ms/step - loss: 0.1406 - accuracy: 0.9772