Edit model card
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

Hugging Face's logo

language: ig datasets:


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


Downloads last month
7
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.