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--- |
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license: cc-by-nc-4.0 |
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language: |
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- gsw |
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- multilingual |
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widget: |
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- text: "Hinder s'Hans-Heiris Huus hani hundert Hase ghöre hueschte." |
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--- |
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The [**google/canine-s**](https://huggingface.co/google/canine-s) model ([Clark et al., TACL 2022](https://aclanthology.org/2022.tacl-1.5/)) trained on Swiss German text data via continued pre-training. |
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## Training Objective |
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We used the CANINE-S objective combined with the subword vocabulary of [SwissBERT](https://huggingface.co/ZurichNLP/swissbert). |
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## Training Data |
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For continued pre-training, we used the following two datasets of written Swiss German: |
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1. [SwissCrawl](https://icosys.ch/swisscrawl) ([Linder et al., LREC 2020](https://aclanthology.org/2020.lrec-1.329)), a collection of Swiss German web text (forum discussions, social media). |
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2. A custom dataset of Swiss German tweets |
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In addition, we trained the model on an equal amount of Standard German data. We used news articles retrieved from [Swissdox@LiRI](https://t.uzh.ch/1hI). |
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## License |
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Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). |
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## Citation |
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```bibtex |
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@inproceedings{vamvas-etal-2024-modular, |
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title={Modular Adaptation of Multilingual Encoders to Written Swiss German Dialect}, |
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author={Jannis Vamvas and No{\"e}mi Aepli and Rico Sennrich}, |
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booktitle={First Workshop on Modular and Open Multilingual NLP}, |
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year={2024}, |
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} |
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``` |
