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---
license: cc-by-sa-3.0
config_names:
- Abbreviation equality
- Adjective inflection analogy
- Clinical analogy
- Clinical similarity
- Noun inflection analogy
- UMNSRS relatedness
- UMNSRS similarity
- Verb inflection analogy
#dataset_info:
#- config_name: Abbreviation equality
# features:
# - name: train
# dtype: string
configs:
- config_name: Abbreviation equality
data_files:
- split: train
path: Abbreviation equality/train*
- config_name: Adjective inflection analogy
data_files:
- split: train
path: Adjective inflection analogy/train*
- config_name: Clinical analogy
data_files:
- split: train
path: Clinical analogy/train*
- config_name: Clinical similarity
data_files:
- split: train
path: Clinical similarity/train*
- config_name: Noun inflection analogy
data_files:
- split: train
path: Noun inflection analogy/train*
- config_name: UMNSRS relatedness
data_files:
- split: train
path: UMNSRS relatedness/train*
- config_name: UMNSRS similarity
data_files:
- split: train
path: UMNSRS similarity/train*
- config_name: Verb inflection analogy
data_files:
- split: train
path: Verb inflection analogy/train*
---
# Danish medical word embeddings
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/).
The embeddings were trained for 10 epochs using a window size of 5 and 10 negative samples.
The development of the corpus and word embeddings is described further in our [paper](https://aclanthology.org/2023.nodalida-1.31/).
We also trained a transformer model on the developed corpus which can be found [here](https://huggingface.co/jannikskytt/MeDa-Bert).
### Citing
```
@inproceedings{pedersen-etal-2023-meda,
title = "{M}e{D}a-{BERT}: A medical {D}anish pretrained transformer model",
author = "Pedersen, Jannik and
Laursen, Martin and
Vinholt, Pernille and
Savarimuthu, Thiusius Rajeeth",
booktitle = "Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)",
month = may,
year = "2023",
address = "T{\'o}rshavn, Faroe Islands",
publisher = "University of Tartu Library",
url = "https://aclanthology.org/2023.nodalida-1.31",
pages = "301--307",
}
```
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