---
license: cc-by-4.0
language:
- tn
library_name: transformers
pipeline_tag: token-classification
tags:
- setswana
- pos
- masakhane-pos
datasets:
- dsfsi/PuoData
metrics:
- f1
---

# PuoBERTa-POS: A Setswana Langage Model Finetuned on MasakhaPOS for Parts of Speech Tagging.

[![Zenodo doi badge](https://img.shields.io/badge/DOI-10.5281%2Fzenodo.8434795-blue.svg)](https://doi.org/10.5281/zenodo.8434795) [![arXiv](https://img.shields.io/badge/arXiv-2310.09141-b31b1b.svg)](https://arxiv.org/abs/2310.09141) 🤗 [https://huggingface.co/dsfsi/PuoBERTa](https://huggingface.co/dsfsi/PuoBERTa)

A Roberta-based language model finetuned on MasakhanePOS for Parts of Speech Tagging.

Based on [https://huggingface.co/dsfsi/PuoBERTa](https://huggingface.co/dsfsi/PuoBERTa)

## Model Details

### Model Description

This is a POS model trained on Setswana based on PuoBERTa and fineruned on MasakhaPOS Setswana.

- **Developed by:** Vukosi Marivate ([@vukosi](https://huggingface.co/@vukosi)), Moseli Mots'Oehli ([@MoseliMotsoehli](https://huggingface.co/@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 [MasakhaPOS](https://github.com/masakhane-io/masakhane-pos) downstream task.

| Model | Test Performance |
|---|---|
| **Multilingual Models** |  |
| AfroLM | 83.8 |
| AfriBERTa | 82.5 |
| AfroXLMR-base | 82.7 |
| AfroXLMR-large | 83.0 |
| **Monolingual Models** |  |
| NCHLT TSN RoBERTa | 82.3 |
| PuoBERTa | **83.4** |
| PuoBERTa+JW300 | 84.1 |

### Usage

Use this model for Part of Speech Tagging for Setswana.
```python

```

## 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](https://dsfsi.github.io/).

Email: vukosi.marivate@cs.up.ac.za

**Enjoy exploring Setswana through AI!**