You can deploy this model and start earning money today!

Davlan/
xlm-roberta-base-finetuned-yoruba

Name: xlm-roberta-base-finetuned-yoruba
Availability: InStock

Views

No views yet

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.

python

>>> 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