Update README.md

README.md

@@ -18,7 +18,75 @@ dataset_info:
     num_examples: 2368
   download_size: 224775
   dataset_size: 847311
+license: afl-3.0
+task_categories:
+- text-classification
+- question-answering
+- sentence-similarity
+language:
+- nl
+tags:
+- healthcare
+pretty_name: PubMedCausal_Dutch
+size_categories:
+- 1K<n<10K
 ---
+
 # Dataset Card for "PubMedCausal_Dutch_translated_with_MariaNMT"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+Translation of the **English** version of [PubMedCausal](https://huggingface.co/datasets/medalpaca/medical_meadow_pubmed_causal),
+to **Dutch** using an [Maria NMT model](https://marian-nmt.github.io/), trained by [Helsinki NLP](https://huggingface.co/Helsinki-NLP/opus-mt-en-nl).
+Note, for reference: Maria NMT is based on [BART](https://huggingface.co/docs/transformers/model_doc/bart), described [here](https://arxiv.org/abs/1910.13461).
+
+
+# Attribution
+
+If you use this dataset please use the following to credit the creators of the Health Advice corpus:
+
+```citation
+@inproceedings{yu-etal-2019-detecting,
+    title = "Detecting Causal Language Use in Science Findings",
+    author = "Yu, Bei  and
+      Li, Yingya  and
+      Wang, Jun",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
+    month = nov,
+    year = "2019",
+    address = "Hong Kong, China",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/D19-1473",
+    doi = "10.18653/v1/D19-1473",
+    pages = "4664--4674",
+}
+```
+
+The creators of the OPUS-MT models:
+```
+@InProceedings{TiedemannThottingal:EAMT2020,
+  author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
+  title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
+  booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
+  year = {2020},
+  address = {Lisbon, Portugal}
+ }
+```
+
+and 
+
+```
+@misc {van_es_2023,
+	author       = { {Bram van Es} },
+	title        = { HealthAdvice_Dutch_translated_with_MariaNMT (Revision ae2436a) },
+	year         = 2023,
+	url          = { https://huggingface.co/datasets/UMCU/HealthAdvice_Dutch_translated_with_MariaNMT },
+	doi          = { 10.57967/hf/1481 },
+	publisher    = { Hugging Face }
+}
+```
+
+# License
+
+For both the Maria NMT model and the original [Helsinki NLP](https://twitter.com/HelsinkiNLP) [Opus MT model](https://huggingface.co/Helsinki-NLP) 
+we did **not** find a license. We also did not find a license for the HealthAdvice corpus. For these reasons we use an academic free license v3. 
+license. If this was in error please let us know and we will add the appropriate licensing promptly.