What is early stopping and how do you configure it?

easy

Answer

$Monitor a validation metric each epoch; stop training when it hasn't improved for 'patience' epochs.$
$Restore the best-performing checkpoint.$
$Prevents overfitting when training beyond the optimal point.$
$Config: choose the right metric (accuracy for classification, F1 for imbalanced, loss for regression), patience ~5-20% of total epochs, and a small delta threshold to avoid stopping on noise.$

Check yourself — multiple choice

Stop training after N steps
Stop when val metric hasn't improved for patience epochs; restore best checkpoint — prevents overfitting
Same as gradient clipping
Only for classification

Early stopping: patience + best-checkpoint restore → avoids overfitting.

#regularization#training

214 interview questions in this topic.