Avoid early stopping while fitting

[talhaanwarch]

Here is my code

config = deeptable.ModelConfig(nets=deepnets.DeepFM)
dt = deeptable.DeepTable(config=config)
model, history = dt.fit(train, y_train,callbacks=None, epochs=200)

I don't want to have early stopping, what should I do?

This might help

2 class detected, {0, 1}, so inferred as a [binary classification] task
Preparing features taken 30.83131170272827s
Imputation taken 18.713809967041016s
Categorical encoding taken 0.0s
Injected a callback [EarlyStopping]. monitor:val_accuracy, patience:1, mode:max
1 Physical GPUs, 1 Logical GPUs

[lixfz]

You can set ModelConfigearlystopping_patience to a larger number:

config = deeptable.ModelConfig(nets=deepnets.DeepFM, earlystopping_patience=999)