Add model cards for FinBERT. (#3331)

* Add a model card for FinBERT

This is a copy of https://github.com/TurkuNLP/FinBERT/blob/master/README.md.

* Added a file for uncased.

* Add metadata for cased.

* Added metadata for uncased.

model_cards/TurkuNLP/bert-base-finnish-cased-v1/README.md

+---
+language: finnish
+---
+
+## Quickstart
+
+**Release 1.0** (November 25, 2019)
+
+Download the models here:
+
+* Cased Finnish BERT Base: [bert-base-finnish-cased-v1.zip](http://dl.turkunlp.org/finbert/bert-base-finnish-cased-v1.zip)
+* Uncased Finnish BERT Base: [bert-base-finnish-uncased-v1.zip](http://dl.turkunlp.org/finbert/bert-base-finnish-uncased-v1.zip)
+
+We generally recommend the use of the cased model.
+
+Paper presenting Finnish BERT: [arXiv:1912.07076](https://arxiv.org/abs/1912.07076)
+
+## What's this?
+
+A version of Google's [BERT](https://github.com/google-research/bert) deep transfer learning model for Finnish. The model can be fine-tuned to achieve state-of-the-art results for various Finnish natural language processing tasks.
+
+FinBERT features a custom 50,000 wordpiece vocabulary that has much better coverage of Finnish words than e.g. the previously released [multilingual BERT](https://github.com/google-research/bert/blob/master/multilingual.md) models from Google:
+
+| Vocabulary | Example |
+|------------|---------|
+| FinBERT    | Suomessa vaihtuu kesän aikana sekä pääministeri että valtiovarain ##ministeri . |
+| Multilingual BERT | Suomessa vai ##htuu kes ##än aikana sekä p ##ää ##minister ##i että valt ##io ##vara ##in ##minister ##i . |
+
+FinBERT has been pre-trained for 1 million steps on over 3 billion tokens (24B characters) of Finnish text drawn from news, online discussion, and internet crawls. By contrast, Multilingual BERT was trained on Wikipedia texts, where the Finnish Wikipedia text is approximately 3% of the amount used to train FinBERT.
+
+These features allow FinBERT to outperform not only Multilingual BERT but also all previously proposed models when fine-tuned for Finnish natural language processing tasks.
+
+## Results
+
+### Document classification
+
+![learning curves for Yle and Ylilauta document classification](https://raw.githubusercontent.com/TurkuNLP/FinBERT/master/img/yle-ylilauta-curves.png)
+
+FinBERT outperforms multilingual BERT (M-BERT) on document classification over a range of training set sizes on the Yle news (left) and Ylilauta online discussion (right) corpora. (Baseline classification performance with [FastText](https://fasttext.cc/) included for reference.)
+
+[[code](https://github.com/spyysalo/finbert-text-classification)][[Yle data](https://github.com/spyysalo/yle-corpus)] [[Ylilauta data](https://github.com/spyysalo/ylilauta-corpus)]
+
+### Named Entity Recognition
+
+Evaluation on FiNER corpus ([Ruokolainen et al 2019](https://arxiv.org/abs/1908.04212))
+
+| Model          | Accuracy |
+|--------------------|----------|
+| **FinBERT**  | **92.40%** |
+| Multilingual BERT | 90.29% |
+| [FiNER-tagger](https://github.com/Traubert/FiNer-rules) (rule-based) | 86.82%      |
+
+(FiNER tagger results from [Ruokolainen et al. 2019](https://arxiv.org/pdf/1908.04212.pdf))
+
+[[code](https://github.com/jouniluoma/keras-bert-ner)][[data](https://github.com/mpsilfve/finer-data)]
+
+### Part of speech tagging
+
+Evaluation on three Finnish corpora annotated with [Universal Dependencies](https://universaldependencies.org/) part-of-speech tags: the Turku Dependency Treebank (TDT), FinnTreeBank (FTB), and Parallel UD treebank (PUD)
+
+| Model             |     TDT     |     FTB     |     PUD     |
+|-------------------|-------------|-------------|-------------|
+| **FinBERT**       | **98.23%**  | **98.39%**  | **98.08%**  |
+| Multilingual BERT |   96.97%    |   95.87%    |   97.58%    |
+
+[[code](https://github.com/spyysalo/bert-pos)][[data](http://hdl.handle.net/11234/1-2837)]
+
+## Use with PyTorch
+
+If you want to use the model with the huggingface/transformers library, follow the steps in [huggingface_transformers.md](https://github.com/TurkuNLP/FinBERT/blob/master/huggingface_transformers.md)
+
+## Previous releases
+
+### Release 0.2
+
+**October 24, 2019** Beta version of the BERT base uncased model trained from scratch on a corpus of Finnish news, online discussions, and crawled data. 
+
+Download the model here: [bert-base-finnish-uncased.zip](http://dl.turkunlp.org/finbert/bert-base-finnish-uncased.zip)
+
+### Release 0.1
+
+**September 30, 2019** We release a beta version of the BERT base cased model trained from scratch on a corpus of Finnish news, online discussions, and crawled data. 
+
+Download the model here: [bert-base-finnish-cased.zip](http://dl.turkunlp.org/finbert/bert-base-finnish-cased.zip)

model_cards/TurkuNLP/bert-base-finnish-uncased-v1/README.md

+---
+language: finnish
+---
+
+## Quickstart
+
+**Release 1.0** (November 25, 2019)
+
+Download the models here:
+
+* Cased Finnish BERT Base: [bert-base-finnish-cased-v1.zip](http://dl.turkunlp.org/finbert/bert-base-finnish-cased-v1.zip)
+* Uncased Finnish BERT Base: [bert-base-finnish-uncased-v1.zip](http://dl.turkunlp.org/finbert/bert-base-finnish-uncased-v1.zip)
+
+We generally recommend the use of the cased model.
+
+Paper presenting Finnish BERT: [arXiv:1912.07076](https://arxiv.org/abs/1912.07076)
+
+## What's this?
+
+A version of Google's [BERT](https://github.com/google-research/bert) deep transfer learning model for Finnish. The model can be fine-tuned to achieve state-of-the-art results for various Finnish natural language processing tasks.
+
+FinBERT features a custom 50,000 wordpiece vocabulary that has much better coverage of Finnish words than e.g. the previously released [multilingual BERT](https://github.com/google-research/bert/blob/master/multilingual.md) models from Google:
+
+| Vocabulary | Example |
+|------------|---------|
+| FinBERT    | Suomessa vaihtuu kesän aikana sekä pääministeri että valtiovarain ##ministeri . |
+| Multilingual BERT | Suomessa vai ##htuu kes ##än aikana sekä p ##ää ##minister ##i että valt ##io ##vara ##in ##minister ##i . |
+
+FinBERT has been pre-trained for 1 million steps on over 3 billion tokens (24B characters) of Finnish text drawn from news, online discussion, and internet crawls. By contrast, Multilingual BERT was trained on Wikipedia texts, where the Finnish Wikipedia text is approximately 3% of the amount used to train FinBERT.
+
+These features allow FinBERT to outperform not only Multilingual BERT but also all previously proposed models when fine-tuned for Finnish natural language processing tasks.
+
+## Results
+
+### Document classification
+
+![learning curves for Yle and Ylilauta document classification](https://raw.githubusercontent.com/TurkuNLP/FinBERT/master/img/yle-ylilauta-curves.png)
+
+FinBERT outperforms multilingual BERT (M-BERT) on document classification over a range of training set sizes on the Yle news (left) and Ylilauta online discussion (right) corpora. (Baseline classification performance with [FastText](https://fasttext.cc/) included for reference.)
+
+[[code](https://github.com/spyysalo/finbert-text-classification)][[Yle data](https://github.com/spyysalo/yle-corpus)] [[Ylilauta data](https://github.com/spyysalo/ylilauta-corpus)]
+
+### Named Entity Recognition
+
+Evaluation on FiNER corpus ([Ruokolainen et al 2019](https://arxiv.org/abs/1908.04212))
+
+| Model          | Accuracy |
+|--------------------|----------|
+| **FinBERT**  | **92.40%** |
+| Multilingual BERT | 90.29% |
+| [FiNER-tagger](https://github.com/Traubert/FiNer-rules) (rule-based) | 86.82%      |
+
+(FiNER tagger results from [Ruokolainen et al. 2019](https://arxiv.org/pdf/1908.04212.pdf))
+
+[[code](https://github.com/jouniluoma/keras-bert-ner)][[data](https://github.com/mpsilfve/finer-data)]
+
+### Part of speech tagging
+
+Evaluation on three Finnish corpora annotated with [Universal Dependencies](https://universaldependencies.org/) part-of-speech tags: the Turku Dependency Treebank (TDT), FinnTreeBank (FTB), and Parallel UD treebank (PUD)
+
+| Model             |     TDT     |     FTB     |     PUD     |
+|-------------------|-------------|-------------|-------------|
+| **FinBERT**       | **98.23%**  | **98.39%**  | **98.08%**  |
+| Multilingual BERT |   96.97%    |   95.87%    |   97.58%    |
+
+[[code](https://github.com/spyysalo/bert-pos)][[data](http://hdl.handle.net/11234/1-2837)]
+
+## Use with PyTorch
+
+If you want to use the model with the huggingface/transformers library, follow the steps in [huggingface_transformers.md](https://github.com/TurkuNLP/FinBERT/blob/master/huggingface_transformers.md)
+
+## Previous releases
+
+### Release 0.2
+
+**October 24, 2019** Beta version of the BERT base uncased model trained from scratch on a corpus of Finnish news, online discussions, and crawled data. 
+
+Download the model here: [bert-base-finnish-uncased.zip](http://dl.turkunlp.org/finbert/bert-base-finnish-uncased.zip)
+
+### Release 0.1
+
+**September 30, 2019** We release a beta version of the BERT base cased model trained from scratch on a corpus of Finnish news, online discussions, and crawled data. 
+
+Download the model here: [bert-base-finnish-cased.zip](http://dl.turkunlp.org/finbert/bert-base-finnish-cased.zip)