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Distilbert Base Uncased Finetuned Conll03 English
A lightweight named entity recognition model based on DistilBERT, optimized for English text and case-insensitive.
Downloads 2,363
Release Time : 3/2/2022
Model Overview
This model is a fine-tuned version of DistilBERT, optimized for Named Entity Recognition (NER) tasks on the CoNLL-2003 English dataset. It can identify entities such as person names, locations, and organizations in text, but is case-insensitive.
Model Features
Lightweight and Efficient
Based on the DistilBERT architecture, it significantly reduces model size while maintaining high performance
Optimized for NER
Fine-tuned specifically for the CoNLL-2003 dataset, excelling at identifying named entities in English text
Case Insensitive
Treats the same word in different cases as the same entity, simplifying processing
Model Capabilities
Named Entity Recognition
Token Classification
English Text Processing
Use Cases
Information Extraction
News Entity Extraction
Automatically identifies people, places, and organization names from news articles
Accuracy reaches 98.5%
Document Analysis
Processes key entity information in legal or business documents
F1 score reaches 98.9%
Data Preprocessing
Knowledge Graph Construction
Preprocesses raw text data for knowledge graph systems
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