[BUGFIX] Fix Race Dataset Checksum bug
I'm not sure this would fix #537 .
However your point about the missing `middle` data is right and we probably want to include these data as well.
Do you think it would we worth having different configurations for this dataset for users who want to only load part of it (`high school` or `middle` or `all`) ? This has fixed #537 at least on my machine hahaha.

Nice point! I think it would totally worth it :) What the best implementation approach would you suggest?

Would it be possible to have `high school`, `middle` and  `all` inside each portion of `train`, `validation` and `test`? Would this make sense? I think we could have one dataset configuration for `high school`, one for `middle` and one for `all`.
You just need to add
```python
    BUILDER_CONFIGS = [
        nlp.BuilderConfig(
            name="high school",
            description="insert description here",
        ),
        nlp.BuilderConfig(
            name="middle",
            description="insert description here",
        ),
        nlp.BuilderConfig(
            name="all",
            description="insert description here",
        ),
    ]
```
as a class attribute for the `Race` class.

Then in `generate_examples` you can check the value of `self.config.name` and choose which files to include when generating examples.

You can check [mlsum](https://github.com/huggingface/nlp/blob/master/datasets/mlsum/mlsum.py) for example if you want to see how it done in general, it's a dataset that has five configurations, and each config has train/val/test splits. Hi @lhoestq sorry for the delay in addressing your comments. Thanks for your assistance :)

You were correct as well, as I was using the script without the `datasets/race/dataset_infos.json` file, it did not verify the checksum. I already fix it as well :)

I managed to get everything running smoothly by now. Please let me know if you think that I could improve my solution
In #537 I noticed that there was a bug in checksum checking when I have tried to download the race dataset. The reason for this is that the current preprocessing was just considering the `high school` data and it was ignoring the `middle` one. This PR just fixes it :)

Moreover, I have added some descriptions.