Add model cards for FinBERT.
These are a copy of https://github.com/TurkuNLP/FinBERT/blob/master/README.md.
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3331?src=pr&el=h1) Report
> Merging [#3331](https://codecov.io/gh/huggingface/transformers/pull/3331?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/20139b7c8d88f380f1e4e0ae2baf0b0ac9351039&el=desc) will **decrease** coverage by `0.06%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/3331/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/3331?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #3331      +/-   ##
==========================================
- Coverage   77.63%   77.57%   -0.07%     
==========================================
  Files         100      100              
  Lines       16943    16943              
==========================================
- Hits        13154    13143      -11     
- Misses       3789     3800      +11     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/3331?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/3331/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `86.40% <0.00%> (-1.97%)` | :arrow_down: |

------

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> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/3331?src=pr&el=footer). Last update [20139b7...d354a22](https://codecov.io/gh/huggingface/transformers/pull/3331?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
<|||||>Great. Could you add a metadata block at the top of the file with:
```
---
language: finnish
# optional thumbnail: ...
---
```

Thanks!<|||||>@haamis I've one question regarding to the FinBERT training corpus: would it be possible to obtain the final pre-processed data that you've used for training the BERT model 🤔

I would really like to train an ELECTRA model and release it to the community :)<|||||>@stefan-it We can't publish the corpus due to licensing/copyright issues, but since we are also interested in training a Finnish ELECTRA maybe we could collaborate on this? Please send me an email sajvir(at)utu.fi.