How to return history of validation loss in Keras

Question

Using Anaconda Python 2.7 Windows 10.

I am training a language model using the Keras exmaple:

print(\'Build model...\')
model = Sequential()
model.ad         


        

Answer 1

Thanks to Alloush,

Following parameter must be included in model.fit():

validation_data = (x_test, y_test)

If it is not defined, val_acc and val_loss will not be exist at output.

Answer 2

The dictionary with histories of "acc", "loss", etc. is available and saved in hist.history variable.

Answer 3

Another option is CSVLogger: https://keras.io/callbacks/#csvlogger. It creates a csv file appending the result of each epoch. Even if you interrupt training, you get to see how it evolved.

Answer 4

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'])