wait_for_everyone

wait_for_everyone.py

accelerator.wait_for_everyone()
unwrapped_best_model = accelerator.unwrap_model(curr_best_model)
if accelerator.is_main_process:
    # this print line is used by tuning jobs to select the best job
    print(f"objective_metric_f1={best_f1};")

    loss_filename, learning_filename, f1_filename = plot_curves(
                                                        train_dataloader.batch_size,
                                                        num_train_epochs,
                                                        learning_rate,
                                                        train_eval_data
                                                    )

    local_best_model_stats = os.path.join(os.getcwd(),'best_model_stats.json')
    with open(local_best_model_stats, "w", encoding="utf-8") as f:
        json.dump({'best_valid_f1': best_f1, 'best_valid_acc':best_acc}, f, ensure_ascii=False, indent=4)

    return unwrapped_best_model, loss_filename, learning_filename, f1_filename, local_best_model_stats