Add the XTREME-S fine-tuning example
# What does this PR do?

This adds and example script and benchmark results for fine-tuning speech models on the [XTREME-S](https://huggingface.co/datasets/google/xtreme_s) becnhmark tasks, namely Speech Recognition and Speech Classification.

The results so far:
| Task                  | Dataset   | Result                | Fine-tuned model & logs                                            | Training time | GPUs   |
|-----------------------|-----------|-----------------------|--------------------------------------------------------------------|---------------|--------|
| Speech Recognition    | MLS       | 30.33 WER             | [here](https://huggingface.co/anton-l/xtreme_s_xlsr_300m_mls/)     | 18:47:25      | 8xV100 |
| Speech Classification | Minds-14  | 94.74 F1 / 94.70 Acc. | [here](https://huggingface.co/anton-l/xtreme_s_xlsr_300m_minds14/) | 04:46:40      | 2xA100 |

_The documentation is not available anymore as the PR was closed or merged._<|||||>Looks very nice! I'm not 100% sure under which folder to put the script, but I tend to `audio-classification` as `run_glue.py` is under `text-classification`. 

This xtreme-s is a new speech benchmark that has both speech recognition, speech translation and speech classification. Think we have the following options:

a) Put it under something like `speech-representation` / `speech-embeddings` because the benchmark is supposed to evaluate exactly this
b) Put it under `audio-classification` similar to `run_glue.py` under text classification
c) ...other ideas? 

@sgugger - any preference? Here a short summary of the benchmark: https://huggingface.co/datasets/patrickvonplaten/xtreme-s (see diagram)