What is the use of verbose in Keras while validating the model?

Question

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 = Bat         


        

Answer 1

For verbose > 0, fit method logs:

• loss: value of loss function for your training data
• acc: accuracy value for your training data.

Note: If regularization mechanisms are used, they are turned on to avoid overfitting.

if validation_data or validation_split arguments are not empty, fit method logs:

• val_loss: value of loss function for your validation data
• val_acc: accuracy value for your validation data

Note: Regularization mechanisms are turned off at testing time because we are using all the capabilities of the network.

For example, using verbose while training the model helps to detect overfitting which occurs if your acc keeps improving while your val_acc gets worse.