Roberta Large Finetuned Ner
R
Roberta Large Finetuned Ner
Developed by romainlhardy
A named entity recognition model fine-tuned on the CoNLL2003 dataset based on the RoBERTa-large model, demonstrating excellent performance in NER tasks.
Downloads 39
Release Time : 6/26/2022
Model Overview
This model is a named entity recognition model based on the RoBERTa-large architecture, specifically optimized for the CoNLL2003 dataset, capable of accurately identifying named entities in text.
Model Features
High-precision entity recognition
Achieves an F1 score of 95.69% on the CoNLL2003 test set, demonstrating outstanding performance.
Based on RoBERTa-large
Utilizes the powerful RoBERTa-large pre-trained model as its foundation, offering rich language understanding capabilities.
End-to-end solution
Provides a complete workflow from text input to entity recognition, requiring no additional processing.
Model Capabilities
Named Entity Recognition
Text token classification
English text processing
Use Cases
Information extraction
News entity extraction
Extracts named entities such as person names, locations, and organization names from news articles.
Can accurately identify various types of named entities.
Knowledge graph construction
Knowledge graph entity recognition
Provides foundational entity recognition for knowledge graph construction.
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