In run_mlm.py the group_texts function incorrectly splits the text into lists of chars
### System Info

```shell
Testing the code for the run_mlm.py - https://github.com/huggingface/transformers/blob/main/examples/pytorch/language-modeling/run_mlm.py to pull it into a separate notebook, I came across an issue with how the group_texts function is being used. Right now it correctly concatenates the input_ids and other lists, but it also operates on the text column (as that is one of the keys in the examples dict()) and incorrectly slices those strings as arrays, based on the token sequence length, which does not apply to the text string length. Further more it produces a list of lists of chars, not a list of strings. I am concerned this may cause issues for the subsequent DataCollatorForLanguageModeling or any downstream classes that rely on the original input text. If this text were tokenized, the function would work but in current code it appears to retain the original text strings.
```


### Who can help?

_No response_

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

``` python
def group_texts(examples):
    # Concatenate all texts.
    concatenated_examples = {k: list(chain(*examples[k])) for k in examples.keys()}
    total_length = len(concatenated_examples[list(examples.keys())[0]])
    # We drop the small remainder, we could add padding if the model supported it instead of this drop, you can
    # customize this part to your needs.
    if total_length >= max_seq_length:
        total_length = (total_length // max_seq_length) * max_seq_length
    # Split by chunks of max_len.
    result = {
        k: [ t[i : i + max_seq_length] for i in range(0, total_length, max_seq_length)]
        for k, t in concatenated_examples.items()
    }
    return result

tokenized_datasets = tokenized_datasets.map(
    group_texts,
    batched=True,
    num_proc=N_CPU,
    load_from_cache_file=True,
    desc=f"Grouping texts in chunks of {max_seq_length}",
)
```

### Expected behavior

```shell
For it to group and concatenate the tokenized_data correctly without messing up the text field.
```

opened in accident, you are deleting that column