Michael-Beukman/NERTransfer
Investigating transfer learning in low-resourced languages, specifically in a named entity recognition (NER) task (IJCNLP-AACL 2023). http://arxiv.org/abs/2309.05311
This project helps natural language processing researchers understand how named entity recognition (NER) models perform across different low-resourced African languages. It takes pre-trained language models and NER datasets in various African languages as input, then fine-tunes and evaluates them. The output includes performance metrics, detailed analyses, and visualizations about how well models transfer knowledge between languages. Researchers focusing on multilingual NLP, especially for African languages, would find this valuable.
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Use this if you are an NLP researcher investigating the effectiveness of transfer learning and zero-shot learning for named entity recognition in low-resourced languages.
Not ideal if you are looking for a ready-to-use NER tool for business applications or a simple API to integrate into an existing product.
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Language
Python
License
Apache-2.0
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Last pushed
Oct 09, 2023
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