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xlm-roberta-base-finetuned-igbo

Model description

xlm-roberta-base-finetuned-igbo is a Igbo RoBERTa model obtained by fine-tuning xlm-roberta-base model on Hausa 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 Igbo 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-igbo')
>>> unmasker("Reno Omokri na Gọọmentị <mask> enweghị ihe ha ga-eji hiwe ya bụ mmachi.")


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 + OPUS CC-Align + IGBO NLP Corpus +Igbo 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 ig_roberta F1
MasakhaNER 84.51 87.74

BibTeX entry and citation info

By David Adelani


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