Append epoch rather than best val. loss to val_loss

[celestinoalan]

Problem

Currently, we're val_loss.append(best_val_loss) in each epoch. This is misleading because we're appending the corresponding epoch (not best across epochs) quantities in train_loss, train_prep, and val_prep. This is also inconvenient, as one often would like to plot both train and validation losses as a function of the epochs to look for overfitting.

Solution

val_loss.append(eval_epoch_loss)

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Thanks for contributing 🎉!

[init27]

Thanks for the great catch-merged!