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Distilbert Base Cased Finetuned Conll03 English
A Named Entity Recognition model based on DistilBERT, fine-tuned on the CoNLL-2003 English dataset, suitable for case-sensitive text processing.
Downloads 7,431
Release Time : 3/2/2022
Model Overview
This model is a variant of DistilBERT, specifically fine-tuned for Named Entity Recognition (NER) tasks. It can identify entities such as person names, locations, and organization names in text, and is case-sensitive.
Model Features
High-precision NER recognition
Achieves an F1 score of 98.7% on the CoNLL-2003 validation set, demonstrating excellent performance.
Case-sensitive
Can distinguish between entities with different cases, such as 'english' and 'English'.
Lightweight model
Based on the DistilBERT architecture, it is smaller and faster than the full BERT model while maintaining high performance.
Model Capabilities
Identify named entities in text
Distinguish case-sensitive entities
Process English text
Use Cases
Information extraction
News article entity extraction
Automatically extract person names, locations, and organization names from news articles
Accurately identifies 98.3% of entities
Document processing
Process entity information in legal or business documents
Data annotation
Automatic annotation tool
Generate preliminary NER annotations for training data
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