group_texts function in language-modeling seems get wrong
During preprocssing of language-modeling, function `group_texts` as https://github.com/huggingface/transformers/blob/main/examples/pytorch/language-modeling/run_mlm.py#L447-L460

seeems ingore the special tokens like [CLS] and [SEP], and just concatenated them together. An obvious bug would appear that one example may have multiple [CLS] tokens that confuses model and also the [CLS] may not be sure to be placed in the first place.
This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.<|||||>I am confused about the efficiency of this function. Does anyone test the performance of trained models by this way?<|||||>I got my except answer from https://github.com/huggingface/transformers/issues/10737, closing this issue.