README.md

metadata

license: cc-by-4.0
language:
  - tn
datasets:
  - dsfsi/PuoData
  - dsfsi/daily-news-dikgang
metrics:
  - f1
library_name: transformers
pipeline_tag: text-classification
tags:
  - iptc

PuoBERTa-News: A Setswana Langauge Model Finetuned for News Categorisation

🤗 https://huggingface.co/dsfsi/PuoBERTa

Give Feedback 📑: DSFSI Resource Feedback Form{:target="_blank"}

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/

0. arts_culture_entertainment_and_media (Botsweretshi, setso, boitapoloso le bobegakgang)
1. crime_law_and_justice (Bosenyi, molao le bosiamisi)
2. disaster_accident_and_emergency_incident (Masetlapelo, kotsi le tiragalo ya maemo a tshoganyetso)
3. economy_business_and_finance (Ikonomi, tsa kgwebo le tsa ditšhelete)
4. education (Thuto)
5. environment (Tikologo)
6. health (Boitekanelo)
7. politics (Dipolotiki)
8. religion_and_belief (Bodumedi le tumelo)
9. 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= {SACAIR 2023 (To Appear)},
  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: [email protected]

Enjoy exploring Setswana through AI!