Week 2: Implementing Callbacks in TensorFlow using the MNIST Dataset

[ai_curious]

Ok, but maybe that always keeps the rule from firing, because logs.get(‘acc’) is always None. Are you ever seeing the early stopping message?

I think I have my answer…

Model training does not stop when accuracy reaches a particular threshold

Hi, For the week 2 assignment titled Week 2: Implementing Callbacks in TensorFlow using the MNIST Dataset I have tried to implement the callback function for tensorflow as shown: class myCallback(tf.keras.callbacks.Callback): # Define the correct function signature for on_epoch_end def on_epoch_end(self, epoch, logs={}): if(logs.get('acc') is not None and logs.get('acc') >= 0.99): print("\nReached 99% accuracy so cancelling training!") …