How to return history of validation loss in Keras

Just an example started from

history = model.fit(X, Y, validation_split=0.33, nb_epoch=150, batch_size=10, verbose=0)

You can use

print(history.history.keys())

to list all data in history.

Then, you can print the history of validation loss like this:

print(history.history['val_loss'])

It's been solved.

The losses only save to the History over the epochs. I was running iterations instead of using the Keras built in epochs option.

so instead of doing 4 iterations I now have

model.fit(......, nb_epoch = 4)

Now it returns the loss for each epoch run:

print(hist.history)
{'loss': [1.4358016599558268, 1.399221191623641, 1.381293383180471, 1.3758836857303727]}

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