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Scideberta Full
S
Scideberta Full
Developed by KISTI-AI
Academic paper-specific language model based on DeBERTa v2 architecture, excelling in scientific literature processing tasks
Downloads 515
Release Time : 3/10/2023
Model Overview
This model is specifically optimized for academic paper abstracts and full texts, achieving SOTA performance in scientific entity recognition tasks, and can adapt to specific domains like biomedicine through continuous learning
Model Features
Scientific literature-specific pretraining
Trained from scratch using 260GB scientific paper dataset (S2ORC), perfectly adapted to academic text features
Continuous learning capability
Can derive specialized sub-models like MediBioDeBERTa through domain adaptation training
Current best performance
Achieves SOTA level in NER tasks on SciERC dataset
Model Capabilities
Scientific literature entity recognition
Biomedical text processing
Academic text feature extraction
Use Cases
Academic research
Scientific entity recognition
Automatically identify professional terms and named entities in papers
Achieves optimal performance on SciERC dataset
Biomedical
Medical literature analysis
Process specialized literature in biomedical field
Derivative model MediBioDeBERTa ranks 11th on BLURB benchmark
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