设置迭代次数gpt-2

时间:2019-09-04 06:09:29

标签: python tensorflow nlp

根据本教程,我很好地调整了gpt-2模型:

https://medium.com/@ngwaifoong92/beginners-guide-to-retrain-gpt-2-117m-to-generate-custom-text-content-8bb5363d8b7f

与关联的GitHub存储库:

https://github.com/nshepperd/gpt-2

我已经能够复制示例,但我的问题是我没有找到设置迭代次数的参数。 基本上,训练脚本每100次迭代显示一个样本,并每1000次迭代保存一个模型版本。但是我没有找到一个参数来训练它(例如5000次迭代)然后关闭它。

培训脚本在这里: https://github.com/nshepperd/gpt-2/blob/finetuning/train.py

编辑:

如cronoik所建议,我正在尝试将for循环替换为while。

我要添加以下更改:

1)添加一个附加参数:

parser.add_argument('--training_steps', metavar='STEPS', type=int, default=1000, help='a number representing how many training steps the model shall be trained for')

2)更改循环:

    try:
        for iter_count in range(training_steps):
            if counter % args.save_every == 0:
                save()

3)使用新参数:

python3 train.py --training_steps 300

但是我收到此错误:

  File "train.py", line 259, in main
    for iter_count in range(training_steps):
NameError: name 'training_steps' is not defined

1 个答案:

答案 0 :(得分:1)

您要做的就是将while True循环修改为for循环:

try:
    #replaced
    #while True:
    for i in range(5000):
        if counter % args.save_every == 0:
            save()
        if counter % args.sample_every == 0:
            generate_samples()
        if args.val_every > 0 and (counter % args.val_every == 0 or counter == 1):
            validation()

        if args.accumulate_gradients > 1:
            sess.run(opt_reset)
            for _ in range(args.accumulate_gradients):
                sess.run(
                    opt_compute, feed_dict={context: sample_batch()})
            (v_loss, v_summary) = sess.run((opt_apply, summaries))
        else:
            (_, v_loss, v_summary) = sess.run(
                (opt_apply, loss, summaries),
                feed_dict={context: sample_batch()})

        summary_log.add_summary(v_summary, counter)

        avg_loss = (avg_loss[0] * 0.99 + v_loss,
                    avg_loss[1] * 0.99 + 1.0)

        print(
            '[{counter} | {time:2.2f}] loss={loss:2.2f} avg={avg:2.2f}'
            .format(
                counter=counter,
                time=time.time() - start_time,
                loss=v_loss,
                avg=avg_loss[0] / avg_loss[1]))

        counter += 1
except KeyboardInterrupt:
    print('interrupted')
    save()