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Davlan/
xlm-roberta-base-finetuned-luganda

Name: xlm-roberta-base-finetuned-luganda
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language: lg datasets:

xlm-roberta-base-finetuned-luganda

Model description

xlm-roberta-base-finetuned-luganda is a Luganda RoBERTa model obtained by fine-tuning xlm-roberta-base model on Luganda 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 Luganda corpus.

Intended uses & limitations

How to use

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

python

>>> from transformers import pipeline
>>> unmasker = pipeline('fill-mask', model='Davlan/xlm-roberta-base-finetuned-luganda')
>>> unmasker("Ffe tulwanyisa abo abaagala okutabangula <mask>, Kimuli bwe yategeezezza.")

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 + BUKKEDDE +Luganda CC-100

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	lg_roberta F1
MasakhaNER	79.69	84.70

BibTeX entry and citation info

By David Adelani