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dsfsi/PuoBERTa-POS
PuoBERTa-POS is a token classification model from dsfsi. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as cc-by-4.0.
[](https://doi.org/10.5281/zenodo.8434795) [](https://arxiv.org/abs/2310.09141) 🤗 https://huggingface.co/dsfsi/PuoBERTa
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From the Hugging Face model README
🤗 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
This is a POS model trained on Setswana based on PuoBERTa and fineruned on MasakhaPOS Setswana.
Performance of models on the MasakhaPOS 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 |
Use this model for Part of Speech Tagging for Setswana.
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}
}
Your contributions are welcome! Feel free to improve the model.
Vukosi Marivate
For more details, reach out or check our website.
Email: [email protected]
Enjoy exploring Setswana through AI!