Fix incorrect max_seq_length bug in pytorch training scripts
# What does this PR do?

Fixes #15181 

Input sequences are not correctly truncated to the correct length in the `run_mlm.py` script. Even if a model can support large sequence lengths (such as 1024 or 2048), the sequences are truncated to the tokenizer's default `model_max_length`. This bug is described [here](https://github.com/huggingface/transformers/issues/15181).

This pull request fixes this bug by comparing the `max_seq_length` passed by the user to the maximum sequence length supported by the model (`config.max_position_embeddings`), and sets `max_seq_length = min(data_args.max_seq_length, config.max_position_embeddings)`

If this is the correct fix, I can make the same change in other pytorch training scripts such as [run_plm.py](https://github.com/huggingface/transformers/blob/9a2dabae7002258e41419491c73dd43ad61b5de7/examples/pytorch/language-modeling/run_plm.py#L363), [run_qa.py](https://github.com/huggingface/transformers/blob/9a2dabae7002258e41419491c73dd43ad61b5de7/examples/pytorch/question-answering/run_qa.py#L333), etc.

## Who can review?

@NielsRogge @LysandreJik @sgugger 
As said on the linked issue, this should not be changed.