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Biobert Base Cased V1.2 Finetuned Ner CRAFT English
Named Entity Recognition model based on BioBERT, fine-tuned on the CRAFT English dataset
Downloads 41
Release Time : 3/14/2022
Model Overview
This model is a Named Entity Recognition model based on the BioBERT architecture, specifically optimized for entity recognition tasks in biomedical texts. After fine-tuning on the CRAFT English dataset, it demonstrates excellent entity recognition performance.
Model Features
Biomedical domain optimization
Based on the BioBERT architecture, specifically pre-trained and optimized for biomedical texts
High-performance entity recognition
After fine-tuning on the CRAFT dataset, the F1 score reached 0.8604, demonstrating outstanding performance
Stable training process
After 4 training epochs, all metrics showed steady improvement, with validation loss remaining at a low level
Model Capabilities
Named Entity Recognition in biomedical texts
Biomedical concept extraction
Scientific literature information extraction
Use Cases
Biomedical research
Gene and protein identification in literature
Automatically identify entities such as genes and proteins from biomedical literature
F1 score reached 0.8604, effectively supporting biomedical information extraction
Scientific literature metadata extraction
Automatically extract key biomedical concepts from scientific literature
Medical information processing
Electronic medical record analysis
Identify important medical terms and concepts from clinical texts
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