The Mechanism Behind Early Stopping

Training loss always drops.
Validation loss tells you when the model begins to memorize noise.

As training continues, the network fits smaller and smaller patterns in the training set.

Some of those patterns aren’t general.
The validation curve rises when the model crosses the point where learning becomes memorization.

Key takeaway❔

Early stopping isn’t a “hack”. It is a direct detection of when your model starts overfitting.