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--- |
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license: cc-by-nc-3.0 |
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language: |
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- da |
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tags: |
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- word embeddings |
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- Danish |
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--- |
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# Danish medical word embeddings |
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MeDa-We was trained on a Danish medical corpus of 123M tokens. The word embeddings are 300-dimensional and are trained using [FastText](https://fasttext.cc/). |
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The embeddings were trained for 10 epochs using a window size of 5 and 10 negative samples. |
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The development of the corpus and word embeddings is described further in our [paper](https://aclanthology.org/2023.nodalida-1.31/). |
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We also trained a transformer model on the developed corpus which can be found [here](https://huggingface.co/indsigt-ai/MeDa-BERT). |
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### Citing |
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``` |
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@inproceedings{pedersen-etal-2023-meda, |
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title = "{M}e{D}a-{BERT}: A medical {D}anish pretrained transformer model", |
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author = "Pedersen, Jannik and |
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Laursen, Martin and |
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Vinholt, Pernille and |
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Savarimuthu, Thiusius Rajeeth", |
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booktitle = "Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)", |
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month = may, |
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year = "2023", |
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address = "T{\'o}rshavn, Faroe Islands", |
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publisher = "University of Tartu Library", |
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url = "https://aclanthology.org/2023.nodalida-1.31", |
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pages = "301--307", |
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} |
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``` |
