Davlan / xlm-roberta-base-finetuned-amharic

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Total runs: 105
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30-day runs: 7
Model's Last Updated: June 06 2021
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Introduction of xlm-roberta-base-finetuned-amharic

Model Details of xlm-roberta-base-finetuned-amharic

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xlm-roberta-base-finetuned-amharic

Model description

xlm-roberta-base-finetuned-amharic is a Amharic RoBERTa model obtained by fine-tuning xlm-roberta-base model on Amharic 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 Amharic 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-hausa')
>>> unmasker("የአሜሪካ የአፍሪካ ቀንድ ልዩ መልዕክተኛ ጄፈሪ ፌልትማን በአራት አገራት የሚያደጉትን <mask> መጀመራቸውን የአሜሪካ የውጪ ጉዳይ ሚንስቴር አስታወቀ።")

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 Amharic CC-100

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 am_roberta F1
MasakhaNER 70.96 77.97
BibTeX entry and citation info

By David Adelani


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xlm-roberta-base-finetuned-amharic is an open source model from GitHub that offers a free installation service, and any user can find xlm-roberta-base-finetuned-amharic on GitHub to install. At the same time, huggingface.co provides the effect of xlm-roberta-base-finetuned-amharic install, users can directly use xlm-roberta-base-finetuned-amharic installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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