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language: pcm datasets:
xlm-roberta-base-finetuned-naija
Model description
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.
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-naija')
>>> unmasker("Another attack on ambulance happen for Koforidua in March <mask> year where robbers kill Ambulance driver")
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 + BBC Pidgin
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 | pcm_roberta F1 |
|---|---|---|
| MasakhaNER | 87.26 | 90.00 |
BibTeX entry and citation info
By David Adelani