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--- |
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language: da |
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widget: |
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- text: En trend, der kan blive ligeså hot som<mask>. |
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tags: |
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- roberta |
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- danish |
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- masked-lm |
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- pytorch |
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license: agpl-3.0 |
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--- |
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# DanskBERT |
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This is DanskBERT, a Danish language model. Note that you should not prepend the mask with a space when using it directly! |
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The model is the best performing base-size model on the [ScandEval benchmark for Danish](https://scandeval.github.io/nlu-benchmark/). |
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DanskBERT was trained on the Danish Gigaword Corpus (Strømberg-Derczynski et al., 2021). |
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DanskBERT was trained using fairseq using the RoBERTa-base configuration. The model was trained with a batch size of 2k, and was trained to convergence for 500k steps using 16 V100 cards for approximately two weeks. |
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If you find this model useful, please cite |
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``` |
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@inproceedings{snaebjarnarson-etal-2023-transfer, |
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title = "{T}ransfer to a Low-Resource Language via Close Relatives: The Case Study on Faroese", |
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author = "Snæbjarnarson, Vésteinn and |
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Simonsen, Annika and |
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Glavaš, Goran and |
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Vulić, Ivan", |
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booktitle = "Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)", |
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month = "may 22--24", |
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year = "2023", |
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address = "Tórshavn, Faroe Islands", |
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publisher = {Link{\"o}ping University Electronic Press, Sweden}, |
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} |
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``` |
