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Ruri Reranker Small

Developed by cl-nagoya
Ruri-Reranker is a reranking model specifically optimized for Japanese text, based on the sentence-transformers architecture, effectively improving the relevance ranking of search results.
Downloads 116
Release Time : 8/19/2024

Model Overview

This model is primarily used for Japanese text reranking tasks, capable of scoring and sorting based on the relevance between queries and documents, suitable for information retrieval systems.

Model Features

Japanese Optimization
Specifically optimized for Japanese text, better handling semantic matching between Japanese queries and documents.
Efficient Performance
Achieves performance comparable to larger models while maintaining a smaller model size.
Multi-Scenario Applicability
Suitable for various information retrieval scenarios, effectively improving the relevance ranking of search results.

Model Capabilities

Text Relevance Scoring
Search Result Reranking
Japanese Semantic Matching

Use Cases

Information Retrieval
Q&A Systems
Used in Q&A systems to rank candidate answers by relevance, improving the ranking of the best answer.
Achieved a score of 64.5 on the JQaRA dataset
Document Retrieval
Reranks returned results in document retrieval systems to improve the ranking of the most relevant documents.
Achieved a score of 92.6 on the JaCWIR dataset
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