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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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+
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+ # 🇹🇷 Turkish ConvBERT model
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+
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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/master/merve_logo.png">
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+ </p>
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+
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+ [![DOI](https://zenodo.org/badge/237817454.svg)](https://zenodo.org/badge/latestdoi/237817454)
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+
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+ We present community-driven BERT, DistilBERT, ELECTRA and ConvBERT models for Turkish 🎉
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+
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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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+
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+ Logo is provided by [Merve Noyan](https://twitter.com/mervenoyann).
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+
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+ # Stats
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+
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+ We've trained an (uncased) ConvBERT 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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+
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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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+
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+ We used the original 32k vocab (instead of creating a new one).
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+
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+ # mC4 ConvBERT
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+
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+ In addition to the ELEC**TR**A base model, we also trained an ConvBERT 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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+
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+ # Model usage
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+
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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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+
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+ Example usage with 🤗/Transformers:
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+
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+ ```python
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+ tokenizer = AutoTokenizer.from_pretrained("dbmdz/convbert-base-turkish-mc4-cased")
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+
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+ model = AutoModel.from_pretrained("dbmdz/convbert-base-turkish-mc4-cased")
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+ ```
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+
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+ # Citation
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+
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+ You can use the following BibTeX entry for citation:
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+
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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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+
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+ # Acknowledgments
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+
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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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+
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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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+
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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 ❤️