Currently I use the following code: callbacks = [ EarlyStopping(monitor='val_loss', patience=2, verbose=0), ModelCheckpoint(kfold_weights_path, monitor='val_loss', save_best_only=True, verbose=0), ] model.fit(X_train.astype('float32'), Y_train, batch_size=batch_size, nb_epoch=nb_epoch, shuffle=True, verbose=1, validation_data=(X_valid, Y_valid), callbacks=callbacks) It tells Keras to stop training when loss didn't improve for 2 epochs. But I want to stop training after loss became smaller than some constant "THR": if val_loss < THR: break I've seen in documentation there are possibility to make your own callback: http://keras.io/callbacks/ But nothing found how to stop training process. I need an advice. Continue reading...
