mc4.py

model.compile(loss = 'categorical_crossentropy',
              optimizer = 'adam',
              metrics = ['accuracy'])

class myCallback(tf.keras.callbacks.Callback):
    def on_epoch_end(self, epoch, logs={}):
        if(logs.get('accuracy')>0.95):
            print("\nReached >95% accuracy so cancelling training!")
            self.model.stop_training = True
        
callbacks = myCallback()