在向其标记器添加一些特殊标记后,我正在尝试微调 Roberta 模型:
special_tokens_dict = {'additional_special_tokens': ['[Tok1]','[Tok2]']}
tokenizer.add_special_tokens(special_tokens_dict)
当我尝试训练模型(在 cpu 上)时出现此错误:
IndexError Traceback (most recent call last)
<ipython-input-75-d63f8d3c6c67> in <module>()
50 l = model(b_input_ids,
51 attention_mask=b_input_mask,
---> 52 labels=b_labels)
53 loss,logits = l
54 total_train_loss += l[0].item()
8 frames
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
1850 # remove once script supports set_grad_enabled
1851 _no_grad_embedding_renorm_(weight, input, max_norm, norm_type)
-> 1852 return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
1853
1854
IndexError: index out of range in self
ps如果我评论add_special_tokens
代码有效。