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Duot5 Base Msmarco
A text re-ranking model based on the T5-base architecture, fine-tuned on the MS MARCO passage dataset to improve the relevance ranking of information retrieval results.
Downloads 4,915
Release Time : 3/2/2022
Model Overview
This model adopts the T5-base architecture and is specifically optimized for result re-ranking in information retrieval tasks. Fine-tuned for 50,000 steps on the MS MARCO passage dataset, it effectively enhances the quality of relevance ranking for retrieval results.
Model Features
Pairwise Re-ranking Capability
Specifically designed to compare and re-rank document pairs, optimizing the relevance of retrieval results.
MS MARCO Fine-tuning
Precisely fine-tuned for 5 training epochs on the large-scale information retrieval dataset MS MARCO.
Sequence-to-Sequence Architecture
Leverages the advantages of T5's sequence-to-sequence architecture to handle text ranking tasks.
Model Capabilities
Document Relevance Scoring
Retrieval Result Re-ranking
Text Pair Comparison
Use Cases
Information Retrieval Systems
Search Engine Result Optimization
Re-ranks initial results returned by search engines to improve the ranking of the most relevant results.
Can significantly enhance the relevance of top-ranked results (specific metrics should refer to the paper).
Question Answering System Enhancement
Ranks candidate answer passages by relevance in question-answering systems.
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