| library_name: transformers | |
| tags: | |
| - politics | |
| - parliamnet | |
| - sentiment-analysis | |
| # Model Card for Model ID | |
| <!-- --> | |
| Fine-tuned BERT trained to identify political party from speech in the UK Parliament. Trained with Labour/Conservative speeches using the hansard dataset 2000-2020 | |
| ## Model Details | |
| - **License:** MIT | |
| - **Finetuned from model :** BERT | |
| ### Model Sources | |
| <!-- Provide the basic links for the model. --> | |
| - **Repository:** [Available on Github](https://github.com/gitvan711/Party-Political-Sentiment-Analysis) | |
| ## Uses | |
| Model can be used to predict whether an item of speech from the UK Parliament was said by a member of the Labour or Conservative Party. | |
| ### Out-of-Scope Use | |
| Model has only been exposed to UK data and speeches from Labour or Conservative. May not work as intended for other parties or geographies. | |
| ### Training Data | |
| [biglam/hansard_speech](https://huggingface.co/datasets/biglam/hansard_speech) | |
| #### Preprocessing | |
| [bert-cased] | |
| ## Evaluation | |
| Evaluated on held-out test data. Achieved test accuracy >80% and test loss <0.4 (binary cross-entropy). | |
| ## Citation | |
| <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> | |
| **BibTeX:** | |
| @misc{baly2020detect, | |
| title={We Can Detect Your Bias: Predicting the Political Ideology of News Articles}, | |
| author={Ramy Baly and Giovanni Da San Martino and James Glass and Preslav Nakov}, | |
| year={2020}, | |
| eprint={2010.05338}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } |