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--- |
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language: pl |
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tags: |
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- herbert |
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license: cc-by-4.0 |
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--- |
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# HerBERT |
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**[HerBERT](https://en.wikipedia.org/wiki/Zbigniew_Herbert)** is a BERT-based Language Model trained on Polish corpora |
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using Masked Language Modelling (MLM) and Sentence Structural Objective (SSO) with dynamic masking of whole words. For more details, please refer to: [HerBERT: Efficiently Pretrained Transformer-based Language Model for Polish](https://www.aclweb.org/anthology/2021.bsnlp-1.1/). |
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Model training and experiments were conducted with [transformers](https://github.com/huggingface/transformers) in version 2.9. |
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## Corpus |
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HerBERT was trained on six different corpora available for Polish language: |
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| Corpus | Tokens | Documents | |
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| :------ | ------: | ------: | |
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| [CCNet Middle](https://github.com/facebookresearch/cc_net) | 3243M | 7.9M | |
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| [CCNet Head](https://github.com/facebookresearch/cc_net) | 2641M | 7.0M | |
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| [National Corpus of Polish](http://nkjp.pl/index.php?page=14&lang=1)| 1357M | 3.9M | |
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| [Open Subtitles](http://opus.nlpl.eu/OpenSubtitles-v2018.php) | 1056M | 1.1M |
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| [Wikipedia](https://dumps.wikimedia.org/) | 260M | 1.4M | |
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| [Wolne Lektury](https://wolnelektury.pl/) | 41M | 5.5k | |
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## Tokenizer |
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The training dataset was tokenized into subwords using a character level byte-pair encoding (``CharBPETokenizer``) with |
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a vocabulary size of 50k tokens. The tokenizer itself was trained with a [tokenizers](https://github.com/huggingface/tokenizers) library. |
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We kindly encourage you to use the ``Fast`` version of the tokenizer, namely ``HerbertTokenizerFast``. |
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## Usage |
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Example code: |
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```python |
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from transformers import AutoTokenizer, AutoModel |
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tokenizer = AutoTokenizer.from_pretrained("allegro/herbert-base-cased") |
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model = AutoModel.from_pretrained("allegro/herbert-base-cased") |
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output = model( |
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**tokenizer.batch_encode_plus( |
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[ |
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( |
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"A potem szedł środkiem drogi w kurzawie, bo zamiatał nogami, ślepy dziad prowadzony przez tłustego kundla na sznurku.", |
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"A potem leciał od lasu chłopak z butelką, ale ten ujrzawszy księdza przy drodze okrążył go z dala i biegł na przełaj pól do karczmy." |
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) |
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], |
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padding='longest', |
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add_special_tokens=True, |
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return_tensors='pt' |
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) |
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) |
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``` |
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## License |
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CC BY 4.0 |
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## Citation |
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If you use this model, please cite the following paper: |
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``` |
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@inproceedings{mroczkowski-etal-2021-herbert, |
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title = "{H}er{BERT}: Efficiently Pretrained Transformer-based Language Model for {P}olish", |
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author = "Mroczkowski, Robert and |
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Rybak, Piotr and |
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Wr{\\'o}blewska, Alina and |
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Gawlik, Ireneusz", |
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booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing", |
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month = apr, |
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year = "2021", |
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address = "Kiyv, Ukraine", |
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publisher = "Association for Computational Linguistics", |
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url = "https://www.aclweb.org/anthology/2021.bsnlp-1.1", |
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pages = "1--10", |
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} |
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``` |
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## Authors |
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The model was trained by [**Machine Learning Research Team at Allegro**](https://ml.allegro.tech/) and [**Linguistic Engineering Group at Institute of Computer Science, Polish Academy of Sciences**](http://zil.ipipan.waw.pl/). |
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You can contact us at: <a href="mailto:klejbenchmark@allegro.pl">klejbenchmark@allegro.pl</a> |
