Update README.md

README.md

@@ -60,4 +60,33 @@ configs:
   - 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",
+}
+```