deep-learning-with-python-notebooks: Training and validation loss plot uses wrong history.history keys

Notebook 3.5-classifying-movie-reviews

The code that is supposed to generate the Training and validation loss side by side uses wrong history.history keys:

acc = history.history['acc'] val_acc = history.history['val_acc'] loss = history.history['loss'] val_loss = history.history['val_loss']

which results in the following errors: KeyError: 'acc' KeyError: 'val_acc'

If you examine de history.history keys you can see that they have different names: history_dict = history.history history_dict.keys()

dict_keys(['loss', 'val_loss', 'binary_accuracy', 'val_binary_accuracy'])

This is probably due to the use of metrics.binary_accuracy as the metric for evaluating the model. The following change in keys would fix the error: acc = history.history['binary_accuracy'] val_acc = history.history['val_binary_accuracy']

About this issue

Original URL
State: open
Created 7 years ago
Reactions: 17
Comments: 17

Most upvoted comments

Hey, for me it was solved by typing ‘accuracy’ instead of ‘acc’ , I was told that its a keras version mismatch. @techSash @seifmahmoud

+11

srina1h on Apr 5, 2020

Hi. I got the key error when I used history.histroy['acc']. So I changed it to history.history['binary_accuracy'] and even that gives me the same error. I am using tensorflow 2.1.0. history.history.keys() return dict_keys(['loss', 'accuracy']). How do I access val_acc and val_loss

I have the same error, is there a fix for this?

@thisiseshan try ‘accuracy’ instead of ‘binary_accuracy’

srina1h on Apr 27, 2020

It is still open because there are lots of us and new students who are struggling with coding (unlike you). Do not follow the thread if it is a waste of your precious time.

On Sat, Aug 22, 2020 at 10:41 PM Aryan Choudhary notifications@github.com wrote:

LOL it is very simple just use print(history.history) and use the output accordingly, I wonder why this issue is still open.

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RorisangSitoboli on Aug 24, 2020