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How to return history of validation loss in Keras

Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about How to return history of validation loss in Keras in Python. So Here I am Explain to you all the possible Methods here.

Without wasting your time, Let’s start This Article.

Table of Contents

How to return history of validation loss in Keras?

  1. How to return history of validation loss in Keras?

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

  2. return history of validation loss in Keras

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

Method 1

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]}

Method 2

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'])

Summery

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.

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