bert-base-japanese-v3-ner-wikipedia-dataset
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Language | Japanese |
| Framework | PyTorch/Transformers |
| Task | Token Classification (NER) |
What is bert-base-japanese-v3-ner-wikipedia-dataset?
This is a specialized Japanese Named Entity Recognition (NER) model that builds upon the cl-tohoku/bert-base-japanese-v3 architecture. It has been fine-tuned using the llm-book/ner-wikipedia-dataset to perform accurate named entity recognition in Japanese text. The model is part of the educational materials featured in Chapter 6 of the "Introduction to Large Language Models" book.
Implementation Details
The model implements a token classification pipeline optimized for Japanese named entity recognition. It utilizes the Transformers library and can be easily deployed using the Hugging Face pipeline API. The model performs entity recognition with high confidence scores, as demonstrated in its ability to identify person names and location names in Japanese text.
- Built on BERT base Japanese v3 architecture
- Fine-tuned on Wikipedia dataset for NER tasks
- Supports simple aggregation strategy for entity recognition
- Implements token classification pipeline
Core Capabilities
- Accurate identification of Japanese named entities
- High-confidence scoring for entity classification
- Support for multiple entity types including person names (人名) and location names (地名)
- Seamless integration with Transformers pipeline
Frequently Asked Questions
Q: What makes this model unique?
This model is specifically optimized for Japanese named entity recognition, built on a robust BERT architecture and fine-tuned with Wikipedia data. Its high download count (60,000+) demonstrates its reliability and usefulness in the Japanese NLP community.
Q: What are the recommended use cases?
The model is ideal for applications requiring Japanese text analysis, particularly for extracting and classifying named entities like person names and locations. It's well-suited for information extraction, content analysis, and text processing systems working with Japanese content.
