convert_tokens_to_string does not conform to its signature
## Environment info
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- `transformers` version: 4.17.0
- Platform: macOS-11.6.4-x86_64-i386-64bit
- Python version: 3.9.10
- PyTorch version (GPU?): 1.11.0 (False)
- Tensorflow version (GPU?): 2.7.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: False
- Using distributed or parallel set-up in script?: False

### Who can help
@SaulLu 
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## Information

Model I am using (Bert, XLNet ...): `AutoModelForQuestionAnswering`

The problem arises when using:
* [x] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)

The tasks I am working on is:
* [x] an official GLUE/SQUaD task: Question Answering
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

Using the official example script (I will omit it, I will just post the result):

```shell
Question: How many pretrained models are available in 🤗 Transformers?
Answer: ['over', ' 32', ' +']
Question: What does 🤗 Transformers provide?
Answer: ['general', ' -', ' purpose', ' architecture', 's']
Question: 🤗 Transformers provides interoperability between which frameworks?
Answer: ['tensor', 'flow', ' 2', '.', ' 0', ' and', ' p', 'yt', 'or', 'ch']
```

Using the model in our context:
```python
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
import torch

tokenizer = AutoTokenizer.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad")
model = AutoModelForQuestionAnswering.from_pretrained("bert-large-uncased-whole-word-masking-finetuned-squad")

text = "Hello my browser is not working, I need help."
questions = [
    "What is the issue?",
    "What is the request?",
]


def extract_answer_idxs(start_logits, end_logits):
    answer_start = torch.argmax(start_logits)
    answer_end = torch.argmax(end_logits) + 1
    return answer_start, answer_end

text = [text] * len(questions)
inputs = tokenizer(questions, text, add_special_tokens=True, return_tensors="pt", max_length=512, truncation=True)
input_ids = inputs["input_ids"].tolist()
outputs = model(**inputs)
idxs = map(
        lambda x, y: extract_answer_idxs(x, y),
        outputs.start_logits,
        outputs.end_logits,
)
answers = list(
    map(
        lambda x, y: tokenizer.convert_tokens_to_string(tokenizer.convert_ids_to_tokens(x[y[0]:y[1]])),
        input_ids,
        (idx for idx in idxs),
    )
)

print(f"Questions: {questions}")
print(f"Answers: {answers}")
```

Result:
```bash
Questions: ['What is the issue?', 'What is the request?']
Answers: [['my', ' browser', ' is', ' not', ' working'], ['help']]
```

(I also tried in a loop fashion and I get the same identical result.)

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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->
```bash
Questions: ['What is the issue?', 'What is the request?']
Answers: ['my browser is not working', 'help']
```

As the [docs](https://huggingface.co/docs/transformers/main/en/internal/tokenization_utils#transformers.PreTrainedTokenizerBase.convert_tokens_to_string) show, I expect a string and not a list of tokens. 
Please notice how whitespaces are somehow introduced in some of the tokens. 
Furthermore, some tokens are split e.g. `['tensor', 'flow', ' 2', '.', ' 0', ' and', ' p', 'yt', 'or', 'ch']`.

I expect `convert_tokens_to_string` to return a `str`, as it was previously.
Seems related to this issue https://github.com/huggingface/transformers/issues/16520<|||||>> Seems related to this issue #16520

Yeah, I see, I was probably opening the issue the same time you were - thanks for linking it to yours.<|||||>> > Seems related to this issue #16520
> 
> Yeah, I see, I was probably opening the issue the same time you were - thanks for linking it to yours.

No problem. On the surface they both look different but it seems like the root issue relates to how tokens are converted to strings. <|||||>Thank you both for sharing your issues :hugs: ! 

You are indeed right, your problem was related to the same issue: a change in the format of the output given by the `decode` method of the `decoders` objects of the `tokenizers` library.

We have for the moment yanked the version of tokenizers 0.12.0 and in the process of releasing a new version 0.12.1 which reverts this change. Using a previous version of 0.12.0 or the future new 0.12.1 should solve this issue.

Sorry again for any problems this may have caused you :blush: <|||||>Thank you. I appreciate the rapid response on this!<|||||>Thank you @SaulLu 🤗 <|||||>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.