---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: instruction
    dtype: string
  - name: input
    dtype: string
  - name: output
    dtype: string
  splits:
  - name: train
    num_bytes: 847311
    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"


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        = { PubMedCausal_Dutch_translated_with_MariaNMT (Revision 14bfca1) },
	year         = 2023,
	url          = { https://huggingface.co/datasets/UMCU/PubMedCausal_Dutch_translated_with_MariaNMT },
	doi          = { 10.57967/hf/1482 },
	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.