Here’s my runner code snippet:
from pytorch_lightning.callbacks import ModelCheckpoint checkpoint_callback = ModelCheckpoint( save_top_k=5, verbose=True, monitor='avg_val_loss', mode='min' ) from pytorch_lightning.callbacks.early_stopping import EarlyStopping early_stop_callback = EarlyStopping( monitor='avg_val_accuracy', min_delta=0.00, patience=10, verbose=True, mode='max' ) model = Model() trainer = Trainer(gpus=1, callbacks=[early_stop_callback], checkpoint_callback=checkpoint_callback) trainer.fit(model)
My above training stops with the output:
Epoch 29: avg_val_loss was not in top 5
Does this mean the
ModelCheckpoint callback also performs some kind of early stopping?
If not, why is my
EarlyStopping callback not being effective?