I have a question, that maybe is very simple, but I can't do it: I have 3 neural networks which are trained with 100 epochs, and I need to save all the history's train displayed at the end in a .txt file (i.e: time: 00s 0ms/step loss:... accuracy:... recall:... etc.), maybe it's easy, but also I need to plot each metric and its val_metric from each epoch and save that plots too, as images I guess (I know that maybe is nonsense to plot at epoch 1,2... but my professor ask us to do that). How can I do that? And, it's possible to save each line of the epoch and under it the correspondig plots in a file? I use Keras to build the model. This is the .compile() function that I use:

   import tensorflow_addons as tfa
   residual_network_1d_model.compile(loss=tf.keras.losses.BinaryCrossentropy(), optimizer=tf.keras.optimizers.Adam(learning_rate=0.001), metrics=[tf.keras.metrics.BinaryAccuracy(
        name='accuracy', dtype=None, threshold=0.5),tf.keras.metrics.Recall(name='Recall'),tf.keras.metrics.Precision(name='Precision'),tfa.metrics.F1Score(num_classes=27,average='macro'),

Thanks for your answers.


1 Answer 1


For the data that is printed to the terminal while training you should be able to use the CSVLogger callback which will save the output to a plain text file. For plotting the metrics you can use the metrics stored in the History object and plot them using a plotting library such as matplotlib and save them using the library specific function for saving the plot (matplotlib.pyplot.savefig for matplotlib).


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