What is the difference between early stopping and model checkpointing in neural network training?

Question

Data Science with Python — Hard

What is the difference between early stopping and model checkpointing in neural network training?

Accepted Answer

Early stopping prevents overfitting by monitoring validation performance and stopping training when improvement halts. Model checkpointing saves model weights at intervals or when validation performance improves, allowing recovery of the best model state.