Davlan / xlm-roberta-base-finetuned-luganda

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Total runs: 51
24-hour runs: 3
7-day runs: 8
30-day runs: 4
Model's Last Updated: June 18 2021
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Introduction of xlm-roberta-base-finetuned-luganda

Model Details of xlm-roberta-base-finetuned-luganda

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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.

>>> 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


Runs of Davlan xlm-roberta-base-finetuned-luganda on huggingface.co

51
Total runs
3
24-hour runs
0
3-day runs
8
7-day runs
4
30-day runs

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