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Monot5 Base Med Msmarco
A document re-ranking model based on the T5-base architecture, fine-tuned on both the MS MARCO and medical-domain MedMARCO datasets to optimize the relevance ranking of retrieval results.
Downloads 153
Release Time : 3/2/2022
Model Overview
This model achieves cross-domain adaptability through two-stage fine-tuning (general domain + medical domain), specifically designed to enhance the relevance of document ranking in information retrieval systems.
Model Features
Cross-domain Adaptability
Through two-stage fine-tuning (general domain: MS MARCO and medical domain: MedMARCO), it combines general applicability with specialized domain performance.
Efficient Fine-tuning
Significant performance improvements achieved with only 10,000 steps (MS MARCO) and 1,000 steps (MedMARCO) of fine-tuning.
Sequence-to-Sequence Architecture Advantage
Leverages T5's encoder-decoder structure to simultaneously process query-document interaction information.
Model Capabilities
Document Relevance Scoring
Retrieval Result Re-ranking
Cross-domain Transfer Learning
Use Cases
Information Retrieval Systems
Search Engine Result Optimization
Re-ranking initial retrieval results by relevance
Improves accuracy of Top-k results
Medical Literature Retrieval
Optimizing retrieval result ranking in specialized medical databases
Enhances the ranking of clinically relevant literature
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