SAS DLPy's EarlyStopping object monitors validation loss with patience=5. A training run progresses through 25 epochs. What does patience=5 specifically mean?
Select an answer to reveal the explanation.
Short Explanation
Here's the deal — patience=5 means you let training run through 5 straight epochs without a validation-loss drop before stopping. If validation loss improves during that window, the counter resets. You then restore the best weights from the lowest validation-loss epoch.
Full Explanation
The five-consecutive-epochs-without-improvement interpretation is correct because patience=5 in early stopping means the trainer waits 5 consecutive epochs without validation loss improvement before stopping training. If validation loss improves at any of those 5 epochs, the patience counter resets. The best model state (lowest validation loss) is typically restored at stopping. The minimum-five-epoch warm-up interpretation is wrong; patience defines the wait window, not a minimum training window. The immediate-trigger-on-first-increase-after-five-epochs interpretation is wrong; early stopping waits 5 consecutive non-improving epochs, not just one. The learning-rate-reduction-by-factor-of-five interpretation describes learning rate scheduling (ReduceLROnPlateau), not early stopping.