Validation loss is your guide during training. Evaluate on held-out data every steps.
Healthy patterns:
- Both training and validation loss decrease together
- Validation loss levels off (normal)
Unhealthy patterns:
- Validation loss increases while training loss decreases (overfitting)
- Both losses flat from the start (learning rate too low or data issues)
Stop training when validation loss stops improving.