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Davlan/xlm-roberta-base-finetuned-naija
xlm-roberta-base-finetuned-naija is a fill-mask model from Davlan. Use it when you need the model to fill a missing word. It is set up for transformers.
Hugging Face's logo --- language: pcm datasets:
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From the Hugging Face model README
language: pcm datasets:
xlm-roberta-base-finetuned-naija is a Nigerian Pidgin RoBERTa model obtained by fine-tuning xlm-roberta-base model on Nigerian Pidgin 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 Nigerian Pidgin corpus.
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-naija')
>>> unmasker("Another attack on ambulance happen for Koforidua in March <mask> year where robbers kill Ambulance driver")
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.
This model was fine-tuned on JW300 + BBC Pidgin
This model was trained on a single NVIDIA V100 GPU
| Dataset | XLM-R F1 | pcm_roberta F1 |
|---|---|---|
| MasakhaNER | 87.26 | 90.00 |
By David Adelani