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Monot5 Large Msmarco 10k
M
Monot5 Large Msmarco 10k
Developed by castorini
A T5-large reranker fine-tuned for 10,000 steps on the MS MARCO passage dataset, excelling on non-MS MARCO datasets
Downloads 168
Release Time : 3/2/2022
Model Overview
This model is an optimized reranker for information retrieval tasks, achieved by fine-tuning the T5-large model, particularly adept at zero-shot document reranking on non-MS MARCO datasets
Model Features
Exceptional zero-shot performance
Outperforms similar models like monot5-large-msmarco on non-MS MARCO datasets
Efficient fine-tuning
Achieves high-quality reranking with just 10,000 training steps (1 training epoch)
Based on T5 architecture
Leverages the powerful T5-large pre-trained model with excellent sequence-to-sequence processing capabilities
Model Capabilities
Document relevance reranking
Zero-shot transfer learning
Information retrieval optimization
Use Cases
Information retrieval
Search engine result optimization
Reranking initial search engine results by relevance
Improves search result relevance and quality
Academic literature retrieval
Optimizing literature search result rankings in academic databases
Helps researchers find the most relevant literature faster
Question answering systems
QA candidate answer ranking
Ranking multiple candidate answers generated by QA systems by quality
Improves QA system accuracy and user experience
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