lemonhu/NER-BERT-pytorch
A PyTorch implementation that fine-tunes BERT for named entity recognition on Chinese MSRA dataset with PER, ORG, LOC entity types.
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This repository provides a PyTorch solution for Named Entity Recognition using Google’s pre-trained BERT model. It fine-tunes a BERT transformer on the MSRA Chinese NER dataset, which contains labeled character sequences with BIO tagging for Person, Organization, Location, and Other entity types. The project supports training and evaluation pipelines with configurable hyperparameters for tokenization, learning rate, and model dimensions.
Frequently asked
- What is lemonhu/NER-BERT-pytorch?
- A PyTorch implementation that fine-tunes BERT for named entity recognition on Chinese MSRA dataset with PER, ORG, LOC entity types.
- Is NER-BERT-pytorch open source?
- Yes — lemonhu/NER-BERT-pytorch is open source, released under the MIT license.
- What language is NER-BERT-pytorch written in?
- lemonhu/NER-BERT-pytorch is primarily written in Python.
- How popular is NER-BERT-pytorch?
- lemonhu/NER-BERT-pytorch has 447 stars on GitHub.
- Where can I find NER-BERT-pytorch?
- lemonhu/NER-BERT-pytorch is on GitHub at https://github.com/lemonhu/NER-BERT-pytorch.