Does EarlyStopping in Keras save the best model?

Question

When using something like:

callbacks = [
    EarlyStopping(patience=15, monitor=\'val_loss\', min_delta=0, mode=\'min\'),
    ModelCheckpoint(\'best-weights.         


        

Answer 1

After the training stops by EarlyStopping callback, the current model may not be the best model with the highest/lowest monitored quantity. As a result a new argument, restore_best_weights, has been introduced in Keras 2.2.3 release for EarlyStopping callback if you would like to restore the best weights:

restore_best_weights: whether to restore model weights from the epoch with the best value of the monitored quantity. If False, the model weights obtained at the last step of training are used.