 Solution

The dashed curve is training accuracy: it continues to rise as optimization adapts to the training observations. The solid curve is testing accuracy: it peaks near 10 epochs and then declines. The widening gap is overfitting.

A sensible choice is about 10 epochs, selected by early stopping at the maximum validation accuracy. In a proper analysis, a validation set rather than the final test set should choose this epoch. Early stopping is an implicit regularization method because it limits how far the parameters can adapt to training-specific noise.

Solved by gpt-5.6-sol high.