我正在使用Keras为神经网络运行50个epoc。
这是我对它的详细回应。
你可以看到Epoc 47（loss: 0.0065 - acc: 0.9980）具有更高的准确性和更低的成本，因此更适合。
我是Keras的新手，并且想知道是否可以在特定的epoc（在这种情况下，epoc 47）中使用模型模型的实例而不是最后一个？
编辑：我不想再用epoc = 47进行训练，这似乎浪费时间和资源。
Epoch 1/50
- 32s - loss: 0.4603 - acc: 0.8541
Epoch 2/50
- 31s - loss: 0.1140 - acc: 0.9655
Epoch 3/50
- 31s - loss: 0.0805 - acc: 0.9754
Epoch 4/50
- 38s - loss: 0.0663 - acc: 0.9792
Epoch 5/50
- 47s - loss: 0.0551 - acc: 0.9829
Epoch 6/50
- 39s - loss: 0.0487 - acc: 0.9846
Epoch 7/50
- 38s - loss: 0.0454 - acc: 0.9853
Epoch 8/50
- 37s - loss: 0.0399 - acc: 0.9873
Epoch 9/50
- 42s - loss: 0.0376 - acc: 0.9881
Epoch 10/50
- 42s - loss: 0.0332 - acc: 0.9896
Epoch 11/50
- 41s - loss: 0.0333 - acc: 0.9893
Epoch 12/50
- 39s - loss: 0.0286 - acc: 0.9911
Epoch 13/50
- 36s - loss: 0.0281 - acc: 0.9905
Epoch 14/50
- 35s - loss: 0.0258 - acc: 0.9918
Epoch 15/50
- 37s - loss: 0.0250 - acc: 0.9915
Epoch 16/50
- 35s - loss: 0.0236 - acc: 0.9920
Epoch 17/50
- 41s - loss: 0.0212 - acc: 0.9932
Epoch 18/50
- 33s - loss: 0.0219 - acc: 0.9928
Epoch 19/50
- 36s - loss: 0.0198 - acc: 0.9935
Epoch 20/50
- 37s - loss: 0.0172 - acc: 0.9941
Epoch 21/50
- 35s - loss: 0.0187 - acc: 0.9938
Epoch 22/50
- 38s - loss: 0.0182 - acc: 0.9939
Epoch 23/50
- 33s - loss: 0.0163 - acc: 0.9945
Epoch 24/50
- 35s - loss: 0.0148 - acc: 0.9949
Epoch 25/50
- 33s - loss: 0.0148 - acc: 0.9951
Epoch 26/50
- 37s - loss: 0.0143 - acc: 0.9951
Epoch 27/50
- 36s - loss: 0.0143 - acc: 0.9949
Epoch 28/50
- 34s - loss: 0.0129 - acc: 0.9958
Epoch 29/50
- 36s - loss: 0.0112 - acc: 0.9962
Epoch 30/50
- 34s - loss: 0.0112 - acc: 0.9961
Epoch 31/50
- 34s - loss: 0.0144 - acc: 0.9954
Epoch 32/50
- 40s - loss: 0.0132 - acc: 0.9952
Epoch 33/50
- 40s - loss: 0.0107 - acc: 0.9964
Epoch 34/50
- 43s - loss: 0.0118 - acc: 0.9958
Epoch 35/50
- 36s - loss: 0.0113 - acc: 0.9961
Epoch 36/50
- 34s - loss: 0.0101 - acc: 0.9963
Epoch 37/50
- 37s - loss: 0.0102 - acc: 0.9966
Epoch 38/50
- 37s - loss: 0.0098 - acc: 0.9965
Epoch 39/50
- 35s - loss: 0.0097 - acc: 0.9966
Epoch 40/50
- 35s - loss: 0.0102 - acc: 0.9963
Epoch 41/50
- 34s - loss: 0.0081 - acc: 0.9972
Epoch 42/50
- 36s - loss: 0.0075 - acc: 0.9976
Epoch 43/50
- 32s - loss: 0.0075 - acc: 0.9975
Epoch 44/50
- 32s - loss: 0.0088 - acc: 0.9971
Epoch 45/50
- 31s - loss: 0.0107 - acc: 0.9968
Epoch 46/50
- 32s - loss: 0.0089 - acc: 0.9970
Epoch 47/50
- 33s - loss: 0.0065 - acc: 0.9980
Epoch 48/50
- 30s - loss: 0.0076 - acc: 0.9975
Epoch 49/50
- 30s - loss: 0.0073 - acc: 0.9978
Epoch 50/50
- 30s - loss: 0.0090 - acc: 0.9971