xlm-roberta-base-finetuned-luganda
is a
Wolof RoBERTa
model obtained by fine-tuning
xlm-roberta-base
model on Wolof 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 Wolof 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-wolof')
>>> unmasker("Màkki Sàll feeñal na ay xalaatam ci mbir yu am solo yu soxal <mask> ak Afrik.")
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 OT
+
OPUS
+ News Corpora (Lu Defu Waxu, Saabal, and Wolof Online)
Training procedure
This model was trained on a single NVIDIA V100 GPU
Eval results on Test set (F-score, average over 5 runs)
Runs of Davlan xlm-roberta-base-finetuned-wolof on huggingface.co
38
Total runs
0
24-hour runs
-2
3-day runs
-1
7-day runs
21
30-day runs
More Information About xlm-roberta-base-finetuned-wolof huggingface.co Model
xlm-roberta-base-finetuned-wolof huggingface.co
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xlm-roberta-base-finetuned-wolof is an open source model from GitHub that offers a free installation service, and any user can find xlm-roberta-base-finetuned-wolof on GitHub to install. At the same time, huggingface.co provides the effect of xlm-roberta-base-finetuned-wolof install, users can directly use xlm-roberta-base-finetuned-wolof installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
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