Result is different...

[jdh3577]

Thank you for your code.
However, when i run code setting only finetune teacher(BERT-base)

# run simple fune-tuning *teacher* by uncommenting below cmd
    argv = get_predefine_argv('glue', 'RTE', 'finetune_teacher')

In argument_parser.py,

    elif mode == 'glue':
        argv = [
                '--task_name', task_name,
                '--bert_model', 'bert-base-uncased',
                '--max_seq_length', '128',
                '--train_batch_size', '32',
                '--learning_rate', '2e-5',
                '--num_train_epochs', '4',
                '--eval_batch_size', '32',
                '--log_every_step', '1',
                '--output_dir', os.path.join(HOME_DATA_FOLDER, f'outputs/KD/{task_name}/teacher_12layer'),
                '--do_train', 'True',
                '--do_eval', 'True',
                '--fp16', 'True',
            ]
        if train_type == 'finetune_teacher':
            argv += [
                '--student_hidden_layers', '12',
                '--kd_model', 'kd',
                '--do_eval', 'True',
                '--alpha', '0.0',    # alpha = 0 is equivalent to fine-tuning for KD
            ]

Result

12/16/2019 06:48:04 - INFO - __main__ -   ***** Eval results *****
12/16/2019 06:48:04 - INFO - __main__ -     acc = 0.5983333333333334
12/16/2019 06:48:04 - INFO - __main__ -     eval_loss = 1.6177796708776595

what is the reason..?

[jdh3577]

This is solved!

[yg33717]

i got same problem, can you tell me how did you solved?
finetune teacher(BERT-base), acc = 0.5696666666666667