label list in MNLI dataset
Author: zhaoruic-intel
Pull request: no

## Environment info

- `transformers` version:
- Platform: centos7.2
- Python version: Python3.6.8
- PyTorch version (GPU?): None
- Tensorflow version (GPU?): None
- Using GPU in script?: None
- Using distributed or parallel set-up in script?: None

### Who can help

Models:

- albert, bert, xlm: @LysandreJik


## Information

Model I am using bert-base-uncased-mnli

The problem arises when using:
* [ ] 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: MNLI
* [ ] my own task or dataset: 

## To reproduce
When processiong label list for MNLI tasks, I noticed lable_list is defined different in Huggingface transformer and Hugging face dataset.

### label list in datasets
If I load my data via datasets:
```
import datasets
from datasets import load_dataset, load_metric

raw_datasets = load_dataset("glue", 'mnli')
print(raw_datasets['validation_matched'].features['label'].names)
```
It returns:
```
['entailment', 'neutral', 'contradiction']
```

And label is also mentioned in document: https://huggingface.co/datasets/glue. 
```
mnli
premise: a string feature.
hypothesis: a string feature.
label: a classification label, with possible values including entailment (0), neutral (1), contradiction (2).
idx: a int32 feature.
```

### label list in transoformers
But in huggingface transformers:
```
processor = transformers.glue_processors['mnli']()
label_list = processor.get_labels()
print(label_list)
```
It returns:
```
['contradiction', 'entailment', 'neutral']
```

### label configs
I checked the config used in datasets which is downloaded from https://raw.githubusercontent.com/huggingface/datasets/1.8.0/datasets/glue/glue.py.

The defination for label_classes is: 
```
label_classes=["entailment", "neutral", "contradiction"],
```

And in transformer master, it is defined in function: https://github.com/huggingface/transformers/blob/15d19ecfda5de8c4b50e2cd3129a16de281dbd6d/src/transformers/data/processors/glue.py#L247

It's confusing that same MNLI tasks uses different label order in datasets and transformers. I'm expecting it should be same on both datasets and transformers.


Comments:
cc @sgugger @lhoestq, and I think @lewtun was also interested in that at some point.

Note that the label_list in Transformers is deprecated and should not be used anymore.

Indeed the order between a model's labels and those in a dataset can differ, which is why we've added a `Dataset.align_labels_with_mapping` function in this PR: https://github.com/huggingface/datasets/pull/2457

Hi @lewtun , @sgugger . Thanks for the quick reply. So label_list won't be supported in tranformers in future, and should be handled by datasets, right? 

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/master/CONTRIBUTING.md) are likely to be ignored.

Hi,
Some of the data in dev_mismatched file doesnt have labels, how should we get accurary from them?