Training loss decreases steadily while validation loss rises after several epochs. Which two changes should be evaluated? Select 2 answers.

1. Appropriate regularization or a less complex model.
2. Delete the validation loss metric.
3. Train indefinitely because lower training loss always proves better generalization.
4. Move validation examples into training and continue reporting them as validation.
5. Early stopping based on validation behavior.