A model's loss and reward curves can look good during training even though its final checkpoint produces nonsensical behavior when tested.

“You do the whole training run. Sometimes the, the loss curves look great, the, the rewards in the training curve look great. You take the final checkpoint, and you start playing around with it, and it makes no sense.”