Im using a neural network implemented with the Keras library and below is the results during training. At the end it prints a test score and a test accuracy. I can't figure out exactly what the score represents, but the accuracy I assume to be the number of predictions that was correct when running the test.
Epoch 1/15 1200/1200 [==============================] - 4s - loss: 0.6815 - acc: 0.5550 - val_loss: 0.6120 - val_acc: 0.7525
Epoch 2/15 1200/1200 [==============================] - 3s - loss: 0.5481 - acc: 0.7250 - val_loss: 0.4645 - val_acc: 0.8025
Epoch 3/15 1200/1200 [==============================] - 3s - loss: 0.5078 - acc: 0.7558 - val_loss: 0.4354 - val_acc: 0.7975
Epoch 4/15 1200/1200 [==============================] - 3s - loss: 0.4603 - acc: 0.7875 - val_loss: 0.3978 - val_acc: 0.8350
Epoch 5/15 1200/1200 [==============================] - 3s - loss: 0.4367 - acc: 0.7992 - val_loss: 0.3809 - val_acc: 0.8300
Epoch 6/15 1200/1200 [==============================] - 3s - loss: 0.4276 - acc: 0.8017 - val_loss: 0.3884 - val_acc: 0.8350
Epoch 7/15 1200/1200 [==============================] - 3s - loss: 0.3975 - acc: 0.8167 - val_loss: 0.3666 - val_acc: 0.8400
Epoch 8/15 1200/1200 [==============================] - 3s - loss: 0.3916 - acc: 0.8183 - val_loss: 0.3753 - val_acc: 0.8450
Epoch 9/15 1200/1200 [==============================] - 3s - loss: 0.3814 - acc: 0.8233 - val_loss: 0.3505 - val_acc: 0.8475
Epoch 10/15 1200/1200 [==============================] - 3s - loss: 0.3842 - acc: 0.8342 - val_loss: 0.3672 - val_acc: 0.8450
Epoch 11/15 1200/1200 [==============================] - 3s - loss: 0.3674 - acc: 0.8375 - val_loss: 0.3383 - val_acc: 0.8525
Epoch 12/15 1200/1200 [==============================] - 3s - loss: 0.3624 - acc: 0.8367 - val_loss: 0.3423 - val_acc: 0.8650
Epoch 13/15 1200/1200 [==============================] - 3s - loss: 0.3497 - acc: 0.8475 - val_loss: 0.3069 - val_acc: 0.8825
Epoch 14/15 1200/1200 [==============================] - 3s - loss: 0.3406 - acc: 0.8500 - val_loss: 0.2993 - val_acc: 0.8775
Epoch 15/15 1200/1200 [==============================] - 3s - loss: 0.3252 - acc: 0.8600 - val_loss: 0.2960 - val_acc: 0.8775
400/400 [==============================] - 0s
Test score: 0.299598811865
Test accuracy: 0.88
Looking at the Keras documentation, I still don't understand what score is. For the evaluate function, it says:
Returns the loss value & metrics values for the model in test mode.
One thing I noticed is that when the test accuracy is lower, the score is higher, and when accuracy is higher, the score is lower.