PuoBERTa-News: A Setswana Langauge Model Finetuned for News Categorisation
🤗 https://huggingface.co/dsfsi/PuoBERTa
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A Roberta-based language model finetuned for News Categorisation.
Based on https://huggingface.co/dsfsi/PuoBERTa
Model Details
Model Description
This is a News Categorisation model for Setswana.
- Developed by: Vukosi Marivate (@vukosi), Moseli Mots'Oehli (@MoseliMotsoehli) , Valencia Wagner, Richard Lastrucci and Isheanesu Dzingirai
- Model type: RoBERTa Model
- Language(s) (NLP): Setswana
- License: CC BY 4.0
News Categories
We use the IPTC news codes https://iptc.org/standards/newscodes/
- arts_culture_entertainment_and_media (Botsweretshi, setso, boitapoloso le bobegakgang)
- crime_law_and_justice (Bosenyi, molao le bosiamisi)
- disaster_accident_and_emergency_incident (Masetlapelo, kotsi le tiragalo ya maemo a tshoganyetso)
- economy_business_and_finance (Ikonomi, tsa kgwebo le tsa ditšhelete)
- education (Thuto)
- environment (Tikologo)
- health (Boitekanelo)
- politics (Dipolotiki)
- religion_and_belief (Bodumedi le tumelo)
- society (Setšhaba)
Training, Dev and Validation dataset https://huggingface.co/datasets/dsfsi/daily-news-dikgang.
Model Performance
Performance of models on Daily News Dikgang dataset
Model | 5-fold Cross Validation F1 | Test F1 |
---|---|---|
Logistic Regression + TFIDF | 60.1 | 56.2 |
NCHLT TSN RoBERTa | 64.7 | 60.3 |
PuoBERTa | 63.8 | 62.9 |
PuoBERTaJW300 | 66.2 | 65.4 |
Usage
Use this model for Part of text classification for Setswana.
Citation Information
Bibtex Reference
@inproceedings{marivate2023puoberta,
title = {PuoBERTa: Training and evaluation of a curated language model for Setswana},
author = {Vukosi Marivate and Moseli Mots'Oehli and Valencia Wagner and Richard Lastrucci and Isheanesu Dzingirai},
year = {2023},
booktitle= {Artificial Intelligence Research. SACAIR 2023. Communications in Computer and Information Science},
url= {https://link.springer.com/chapter/10.1007/978-3-031-49002-6_17},
keywords = {NLP},
preprint_url = {https://arxiv.org/abs/2310.09141},
dataset_url = {https://github.com/dsfsi/PuoBERTa},
software_url = {https://huggingface.co/dsfsi/PuoBERTa}
}
Contributing
Your contributions are welcome! Feel free to improve the model.
Model Card Authors
Vukosi Marivate
Model Card Contact
For more details, reach out or check our website.
Email: vukosi.marivate@cs.up.ac.za
Enjoy exploring Setswana through AI!
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