Distilroberta Base Ner Wikiann
A named entity recognition model fine-tuned on the wikiann dataset based on the DistilRoBERTa-base model, used for identifying named entities in text.
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Release Time : 3/2/2022
Model Overview
This model is a lightweight version based on DistilRoBERTa-base, fine-tuned on the wikiann dataset, specifically designed for named entity recognition tasks.
Model Features
Efficient and Lightweight
Lightweight architecture based on DistilRoBERTa, reducing computational resource requirements while maintaining performance.
High-precision Recognition
Achieves an F1 score of 83.78% on the wikiann test set, demonstrating excellent performance.
Multilingual Support
Trained on the multilingual wikiann dataset, supporting named entity recognition in multiple languages.
Model Capabilities
Named Entity Recognition
Text Token Classification
Multilingual Text Processing
Use Cases
Information Extraction
News Article Entity Recognition
Extract entity information such as person names, locations, and organization names from news articles.
Accuracy approximately 92%
Social Media Text Analysis
Analyze entity information in social media texts for user profiling.
Knowledge Graph Construction
Knowledge Graph Entity Extraction
Extract entities from unstructured text for knowledge graph construction.
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