INNER CODE UNIT · Python

eval_loss

microsoft/AzureML-BERT · finetune/run_classifier_azureml.py:136

        eval_loss = eval_loss / nb_eval_steps
        result = compute_metrics(task_name, preds, all_label_ids.numpy())
        loss = tr_loss/nb_tr_steps if args.do_train else None

        result['eval_loss'] = eval_loss
        result['global_step'] = global_step
        result['loss'] = loss
        logger.info("***** Evaluation results *****")
        for key in sorted(result.keys()):
            logger.info("Epoch %s:  %s = %s", epoch_num,
                        key, str(result[key]))
            if(epoch_num  ==2):
                run.log(key, str(result[key]))
    if set_type == "test":
        output_eval_file = os.path.join(args.output_dir, f"{task_name.upper()}-{args.seed}-{args.learning_rate}-ep-{epoch_num}-tot-epochs-{args.num_train_epochs}.tsv")
        with open(output_eval_file, "w") as writer:
            writer.write("index\tprediction\n")
            for i, sample in enumerate(examples):

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