Fine-tuning jobs support early stopping based on validation loss

Fine-tuning jobs now support early stopping, which halts training when validation loss stops improving. This reduces cost and helps avoid overfitting on long runs.

Enable it by setting early_stopping_enabled=true on job creation along with a validation_file and n_evals >= early_stopping_patience + early_stopping_warmup_evals + 1. Tune behavior with early_stopping_patience, early_stopping_min_delta, and early_stopping_warmup_evals.

When training halts early, the job still finishes with status completed. The response sets early_stopped=true and exposes the winning checkpoint via early_stopping_best_step and early_stopping_best_metric.

See Early stopping for details.