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Cv Parser
C
Cv Parser
Developed by nhanv
A named entity recognition model fine-tuned based on microsoft/mdeberta-v3-base, demonstrating outstanding performance on evaluation datasets
Downloads 45
Release Time : 11/29/2022
Model Overview
This model is a named entity recognition model fine-tuned from microsoft/mdeberta-v3-base, excelling at identifying specific types of entities from text
Model Features
High-precision recognition
Achieves 0.89 precision and 0.93 recall on evaluation datasets
Efficient training
Reaches excellent performance after just 10 training epochs
Based on DeBERTa-v3
Utilizes the advanced DeBERTa-v3 architecture with powerful text understanding capabilities
Model Capabilities
Text entity recognition
Named entity extraction
Sequence labeling
Use Cases
Information extraction
Resume information extraction
Automatically identifies entities such as names, skills, and work experience from resume text
Accuracy as high as 98.51%
Medical record processing
Identifies entities like diseases, medications, and symptoms in medical texts
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