songci数据集，wiki2预训练时会报错，生成的掩码pt文件wiki_train_mlNone_rs2022_mr15_mtr8_mtur5.pt只有1k

[Phil-521]

注意，正在使用本地MyTransformer中的MyMultiHeadAttention实现

[2022-11-27 15:03:35] - INFO: ## 使用token embedding中的权重矩阵作为输出层的权重！torch.Size([30522, 768])
[2022-11-27 15:03:38] - INFO: 缓存文件 /home/********/博一/my_explore/BERT_learn/BertWithPretrained-main/data/WikiText/wiki_test_mlNone_rs2022_mr15_mtr8_mtur5.pt 不存在，重新处理并缓存！

正在读取原始数据: 100%|██████████████| 4358/4358 [00:00<00:00, 11122.89it/s]

正在构造NSP和MLM样本(test): 100%|██| 1847/1847 [00:00<00:00, 1681180.44it/s]

[2022-11-27 15:03:38] - INFO: 缓存文件 /home/********/博一/my_explore/BERT_learn/BertWithPretrained-main/data/WikiText/wiki_train_mlNone_rs2022_mr15_mtr8_mtur5.pt 不存在，重新处理并缓存！

正在读取原始数据: 100%|████████████| 36718/36718 [00:03<00:00, 11100.30it/s]

正在构造NSP和MLM样本(train): 100%|█| 15496/15496 [00:00<00:00, 1615704.25it/

Traceback (most recent call last):
File "TaskForPretraining.py", line 300, in
train(config)
File "TaskForPretraining.py", line 105, in train
val_file_path=config.val_file_path)
File "../utils/create_pretraining_data.py", line 334, in load_train_val_test_data
collate_fn=self.generate_batch)
File "/home/pgrad/.conda/envs/wmc_transformer/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 213, in init
sampler = RandomSampler(dataset)
File "/home/pgrad/.conda/envs/wmc_transformer/lib/python3.7/site-packages/torch/utils/data/sampler.py", line 94, in init
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0

[haidequanbu]

遇到同样的问题，请问老哥你解决了吗？

[haidequanbu]

已解决可以看我另外一个issuehttps://github.com/moon-hotel/BertWithPretrained/issues/15
issuse15，复制到浏览器打开

[moon-hotel]

这个问题得你自己去排除一下，我没有遇到过。 感觉像是你这个PyTorch版本多了一个num_samples参数？

[yfzsj01]

应该是数据集切分的问题，跑wiki数据集时设置ModelConfig.seps='.'