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---
license: lgpl
language:
- en
- de
- es
- ca
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- stance
- classification
- pytorch
- multilingual
---
## Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** Cristina España-Bonet
- **Model type:** Binary stance classifier on top of XLM-RoBERTa
- **Language(s) (NLP):** English, German and Spanish
- **License:** LGPL
- **Finetuned from model:** XLM-RoBERTa Large
## Model Sources
<!-- Provide the basic links for the model. -->
- **Repository:** https://github.com/cristinae/docTransformer
- **Data:** https://zenodo.org/records/8417761
- **Paper:** https://aclanthology.org/2023.findings-emnlp.787/
## Direct Use
Determine the political stance of a (newspaper) article. Binary classification: left vs. right stance
#### Evaluation
```srun --ntasks 1 --gpus-per-task 1 python -u docClassifier.py --task evaluation -f ./ -o politicalStanceLvsR_en.bin --test_dataset your.test```
#### Classification
```srun --ntasks 1 --gpus-per-task 1 python -u docClassifier.py --task classification -f ./ -o politicalStanceLvsR_en.bin --test_dataset your.test```
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
```
@inproceedings{espana-bonet:2023,
title = "Multilingual Coarse Political Stance Classification of Media. The Editorial Line of a {C}hat{GPT} and Bard Newspaper",
author = "Espa{\~n}a-Bonet, Cristina",
editor = "Bouamor, Houda and Pino, Juan and Bali, Kalika",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2023",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-emnlp.787",
doi = "10.18653/v1/2023.findings-emnlp.787",
pages = "11757--11777"
}
```
**APA:**
España-Bonet, Cristina. (2023, December). Multilingual Coarse Political Stance Classification of Media. The Editorial Line of a ChatGPT and Bard Newspaper. In Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 11757-11777).