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: yo datasets:


xlm-roberta-base-finetuned-yoruba

Model description

xlm-roberta-base-finetuned-yoruba is a Yoruba RoBERTa model obtained by fine-tuning xlm-roberta-base model on Yorùbá language texts. It provides better performance than the XLM-RoBERTa on text classification and named entity recognition datasets.

Specifically, this model is a xlm-roberta-base model that was fine-tuned on Yorùbá 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-yoruba')
>>> unmasker("Arẹmọ Phillip to jẹ ọkọ <mask> Elizabeth to ti wa lori aisan ti dagbere faye lẹni ọdun mọkandilọgọrun")
                    
[{'sequence': '<s> Arẹmọ Phillip to jẹ ọkọ Queen Elizabeth to ti wa lori aisan ti dagbere faye lẹni ọdun mọkandilọgọrun</s>', 'score': 0.24844281375408173, 
'token': 44109, 
'token_str': '▁Queen'}, 
{'sequence': '<s> Arẹmọ Phillip to jẹ ọkọ ile Elizabeth to ti wa lori aisan ti dagbere faye lẹni ọdun mọkandilọgọrun</s>', 'score': 0.1665010154247284, 
'token': 1350, 
'token_str': '▁ile'}, 
{'sequence': '<s> Arẹmọ Phillip to jẹ ọkọ ti Elizabeth to ti wa lori aisan ti dagbere faye lẹni ọdun mọkandilọgọrun</s>', 'score': 0.07604238390922546, 
'token': 1053, 
'token_str': '▁ti'}, 
{'sequence': '<s> Arẹmọ Phillip to jẹ ọkọ baba Elizabeth to ti wa lori aisan ti dagbere faye lẹni ọdun mọkandilọgọrun</s>', 'score': 0.06353845447301865, 
'token': 12878, 
'token_str': '▁baba'}, 
{'sequence': '<s> Arẹmọ Phillip to jẹ ọkọ Oba Elizabeth to ti wa lori aisan ti dagbere faye lẹni ọdun mọkandilọgọrun</s>', 'score': 0.03836742788553238, 
'token': 82879, 
'token_str': '▁Oba'}]


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 Bible, JW300, Menyo-20k, Yoruba Embedding corpus and CC-Aligned, Wikipedia, news corpora (BBC Yoruba, VON Yoruba, Asejere, Alaroye), and other small datasets curated from friends.

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 yo_roberta F1
MasakhaNER 77.58 83.66
BBC Yorùbá Textclass

BibTeX entry and citation info

By David Adelani


Downloads last month
9
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.

Model tree for Davlan/xlm-roberta-base-finetuned-yoruba

Finetunes
1 model