PuoBERTa-NER / README.md
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metadata
license: cc-by-4.0
datasets:
  - masakhane/masakhaner2
  - dsfsi/PuoData
language:
  - tn
metrics:
  - f1
library_name: transformers
pipeline_tag: token-classification
tags:
  - ner
  - african nlp
  - africanlp

PuoBERTa-NER: A Setswana Langage Model Finetuned on MasakhaNER-2 for Named Entity Recognition.

Zenodo doi badge arXiv 🤗 https://huggingface.co/dsfsi/PuoBERTa

A Roberta-based language model finetuned on MasakhaneNER-2 for Named Entity Recognition.

Based on https://huggingface.co/dsfsi/PuoBERTa

Model Details

Model Description

This is a POS model trained on Setswana based on PuoBERTa and fineruned on MasakhaNER-2 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

Model Performance

Performance of models on the MasakhaNER-2 downstream task.

Model Test Performance (f1 score)
Multilingual Models
AfriBERTa 83.2
AfroXLMR-base 87.7
AfroXLMR-large 89.4
Monolingual Models
NCHLT TSN RoBERTa 74.2
PuoBERTa 78.2
PuoBERTa+JW300 80.2

Usage

Use this model for Part of Speech Tagging for Setswana.


Citation Information

Bibtex Refrence

@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: [email protected]

Enjoy exploring Setswana through AI!