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language: rw datasets:

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xlm-roberta-base-finetuned-kinyarwanda

Model description

xlm-roberta-base-finetuned-kinyarwanda is a Kinyarwanda RoBERTa model obtained by fine-tuning xlm-roberta-base model on Kinyarwanda language texts. It provides better performance than the XLM-RoBERTa on named entity recognition datasets.

Specifically, this model is a xlm-roberta-base model that was fine-tuned on Kinyarwanda corpus.

Intended uses & limitations

How to use

You can use this model with Transformers pipeline for masked token prediction.

>>> from transformers import pipeline
>>> unmasker = pipeline('fill-mask', model='Davlan/xlm-roberta-base-finetuned-kinyarwanda')
>>> unmasker("Twabonye ko igihe mu <mask> hazaba hari ikirango abantu bakunze")

Limitations and bias

This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains.

Training data

This model was fine-tuned on JW300 + KIRNEWS + BBC Gahuza

Training procedure

This model was trained on a single NVIDIA V100 GPU

Eval results on Test set (F-score, average over 5 runs)

Dataset	XLM-R F1	rw_roberta F1
MasakhaNER	73.22	77.76

BibTeX entry and citation info

By David Adelani