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--- |
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language: tr |
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license: mit |
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datasets: |
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- allenai/c4 |
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--- |
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# πΉπ· Turkish ELECTRA model |
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<p align="center"> |
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<img alt="Logo provided by Merve Noyan" title="Awesome logo from Merve Noyan" src="https://raw.githubusercontent.com/stefan-it/turkish-bert/updates/merve_logo.png"> |
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</p> |
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[![DOI](https://zenodo.org/badge/237817454.svg)](https://zenodo.org/badge/latestdoi/237817454) |
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We present community-driven BERT, DistilBERT, ELECTRA and ConvBERT models for Turkish π |
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Some datasets used for pretraining and evaluation are contributed from the |
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awesome Turkish NLP community, as well as the decision for the BERT model name: BERTurk. |
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Logo is provided by [Merve Noyan](https://twitter.com/mervenoyann). |
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# Stats |
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We've also trained an ELECTRA (cased) model on the recently released Turkish part of the |
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[multiligual C4 (mC4) corpus](https://github.com/allenai/allennlp/discussions/5265) from the AI2 team. |
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After filtering documents with a broken encoding, the training corpus has a size of 242GB resulting |
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in 31,240,963,926 tokens. |
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We used the original 32k vocab (instead of creating a new one). |
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# mC4 ELECTRA |
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In addition to the ELEC**TR**A base model, we also trained an ELECTRA model on the Turkish part of the mC4 corpus. We use a |
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sequence length of 512 over the full training time and train the model for 1M steps on a v3-32 TPU. |
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# Model usage |
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All trained models can be used from the [DBMDZ](https://github.com/dbmdz) Hugging Face [model hub page](https://huggingface.co/dbmdz) |
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using their model name. |
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Example usage with π€/Transformers: |
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```python |
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tokenizer = AutoTokenizer.from_pretrained("dbmdz/electra-small-turkish-mc4-cased-discriminator") |
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model = AutoModel.from_pretrained("dbmdz/electra-small-turkish-mc4-cased-discriminator") |
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``` |
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# Citation |
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You can use the following BibTeX entry for citation: |
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```bibtex |
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@software{stefan_schweter_2020_3770924, |
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author = {Stefan Schweter}, |
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title = {BERTurk - BERT models for Turkish}, |
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month = apr, |
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year = 2020, |
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publisher = {Zenodo}, |
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version = {1.0.0}, |
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doi = {10.5281/zenodo.3770924}, |
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url = {https://doi.org/10.5281/zenodo.3770924} |
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} |
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``` |
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# Acknowledgments |
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Thanks to [Kemal Oflazer](http://www.andrew.cmu.edu/user/ko/) for providing us |
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additional large corpora for Turkish. Many thanks to Reyyan Yeniterzi for providing |
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us the Turkish NER dataset for evaluation. |
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We would like to thank [Merve Noyan](https://twitter.com/mervenoyann) for the |
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awesome logo! |
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Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC). |
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Thanks for providing access to the TFRC β€οΈ |
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