Addition of  SequenceClassification config specific documentation to XModelForSequenceClassification.
Author: nasheedyasin
Pull request: no

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version:
- Platform: Windows 10
- Python version: 3.6.12
- Tensorflow version (GPU?): 2.3.1
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help: @sgugger
<!-- Your issue will be replied to more quickly if you can figure out the right person to tag with @
 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

Model hub:

- for issues with a model report at https://discuss.huggingface.co/ and tag the model's creator.

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->

## Information

Model I am using (DistilBert, Longformer):

The tasks I am working on is:
* [ ] my own task or dataset:
A document classification task with 2 or more custom classes.

## To reproduce

Steps to reproduce the behavior:

1. Navigate to the documentation of any [transformers.XForSequenceClassification](https://huggingface.co/transformers/model_doc/longformer.html#transformers.LongformerForSequenceClassification)
2. You will notice an absence of documentation for setting of any Sequence Classification related configs.
3. For example: `id2label, label2id, num_labels`


<!-- If you have code snippets, error messages, stack traces please provide them here as well.
     Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
     Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.-->

## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

Documentation for SequenceClassification specific settings like: `id2label, label2id, num_labels` in the documentation page for  [transformers.XForSequenceClassification](https://huggingface.co/transformers/model_doc/longformer.html#transformers.LongformerForSequenceClassification)
Additionally in the documentation of the  `from_pretrained` method, when loading models fine-tuned on non `SequenceClassification` tasks.


Comments:
Those are generic config parameters and as such, they can't be documented on a model (they are config parameters, not model parameters). The documentation is in the [config page](https://huggingface.co/transformers/main_classes/configuration.html).

The documentation of the `from_pretrained` [method](https://huggingface.co/transformers/main_classes/model.html#transformers.PreTrainedModel.from_pretrained) also tells the user any parameter of the config can be passed to this method as a kwarg.

Understood, the params in question are mentioned there in detail. Thanks 👍🏽 @sgugger