What is the use of verbose in Keras while validating the model?
I'm running the LSTM model for the first time. Here is my model:
opt = Adam(0.002) inp = Input(...) print(inp) x = Embedding(....)(inp) x = LSTM(...)(x) x = BatchNormalization()(x) pred = Dense(5,activation='softmax')(x) model = Model(inp,pred) model.compile(....) idx = np.random.permutation(X_train.shape) model.fit(X_train[idx], y_train[idx], nb_epoch=1, batch_size=128, verbose=1)
What is the use of verbose while training the model?
Check documentation for model.fit here.
By setting verbose 0, 1 or 2 you just say how do you want to 'see' the training progress for each epoch.
verbose=0 will show you nothing (silent)
verbose=1 will show you an animated progress bar like this:
verbose=2 will just mention the number of epoch like this: