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def on_epoch_end(self, epoch, logs={}): if(logs.get('loss')<0.4): print("\nReached 60% accuracy so cancelling training!") self.model.stop_training = True
Im new but shouldn't it be accuracy? something like this?
def on_epoch_end(self, epoch, logs={}): if(logs.get('accuracy') > 0.85): print("\nReached 85% accuracy so cancelling training!") self.model.stop_training = True
with the metrics added to the compile line model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',metrics=['accuracy'])
edit lol just watched the next video shouldn't it just say print("\nReached loss < 0.4 so cancelling training!")
The text was updated successfully, but these errors were encountered:
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def on_epoch_end(self, epoch, logs={}):
if(logs.get('loss')<0.4):
print("\nReached 60% accuracy so cancelling training!")
self.model.stop_training = True
Im new but shouldn't it be accuracy? something like this?
def on_epoch_end(self, epoch, logs={}):
if(logs.get('accuracy') > 0.85):
print("\nReached 85% accuracy so cancelling training!")
self.model.stop_training = True
with the metrics added to the compile line
model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',metrics=['accuracy'])
edit lol just watched the next video
shouldn't it just say print("\nReached loss < 0.4 so cancelling training!")
The text was updated successfully, but these errors were encountered: