Early stopping
A regularizer that monitors a validation metric during training and halts once it has not improved for a set number of epochs (the patience), then restores the best checkpoint. It limits how long the model has to memorize the training set.
Example
With patience = 5, validation loss bottoms out at epoch 12 and fails to improve through epoch 17, so training stops at 17 and the weights from epoch 12 are restored.