--- license: lgpl language: - en - de - es - ca metrics: - accuracy pipeline_tag: text-classification tags: - stance - classification - pytorch - multilingual --- ## Model Description - **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 - **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] **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).