how to create a custom callback function in keras while training the model

Solutions on MaxInterview for how to create a custom callback function in keras while training the model by the best coders in the world

Search
showing results for - "how to create a custom callback function in keras while training the model"
Amelie
29 Mar 2019
1class myCallback(tf.keras.callbacks.Callback):
2  def on_epoch_end(self, epoch, logs={}):
3    if(logs.get('acc')>0.99):
4      print("\nReached 99% accuracy so cancelling training!",epoch)
5      self.model.stop_training = True
6callback=myCallback()
7model.fit(x_training, y_training,callbacks=[callback])
similar questions
keras declare functional modelhow to set learning rate in kerashow to save the history of keras modelplotting keras model trainning historyhow to load a keras model with custom loss functionmetrics for keras modelkeras fit verbosedefault stride value in kerasrename last layer of keras modelkeras callbacksserialize keras modelkeras functional api embedding layersave model with best validation loss kerashow to use keras model with sklearnkeras ann codekeras custom training loopkeras train on batchkeras transfer learningkeras load model with custom objectsclone keras modelkeras callbacks history
queries leading to this page
put callbacks in own model keraskeras custom callback examplehow to create a custom callback function in keras while training the modelcustom callbacks in kerascustom callbacks kerascustom callback function kerashow to create a custom callback function in keras while training the model