Keras Deep Learning Cookbook

Training

1. Running the training, we use rmsprop optimizer and categorical_crossentropy as the loss function:

# Run training model.compile(optimizer='rmsprop', loss='categorical_crossentropy') model.fit([encoder_input_data, decoder_input_data], decoder_target_data,           batch_size=batch_size,           epochs=epochs,           validation_split=0.2) # Save model model.save('/deeplearning-keras/ch09/summarization/model2.h5')

The output will be as follows:

64/800 [=>............................] - ETA: 22:05 - loss: 2.1460128/800 [===>..........................] - ETA: 18:51 - loss: 2.1234192/800 [======>.......................] - ETA: 16:36 - loss: 2.0878256/800 [========>.....................] - ETA: 14:38 - loss: 2.1215320/800 [===========>..................] - ETA: ...