polish-reranker-roberta-v3

模型介绍

This model is designed to serve as a Polish reranker in retrieval-augmented generation (RAG) pipelines. It is a general-purpose reranker that delivers strong performance across various document types and domains. It is the successor to **sdadas/polish-reranker-roberta-v2** and has the following key features: The main difference between **polish-reranker-roberta-v2** and **polish-reranker-roberta-v3** is the support for longer contexts - 16x increase from 512 to 8192 tokens. This has a significant impact on reranking quality for datasets with longer documents. Table 1 presents examples of tasks from the PIRB benchmark where substantial improvements were observed as a result of the extended context. For short and medium-length texts, the model achieves comparable or slightly better results than the previous version. For tasks involving very short texts (e.g., *onet*, *czy-wiesz-v2*), we observed a slight decrease in quality. The average score on the PIRB benchmark increased from **64.49** to **65.17** when using the sdadas/mmlw-retrieval-roberta-large retriever, or from **65.30** to **66.21** when using BAAI/bge-multilingual-gemma2. Task Improvement using sdadas/mmlw-retrieval-roberta-large retriever Improvement using BAAI/bge-multilingual-gemma2 retriever

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

常见问题

资料来源与可追溯记录

许可证：gemma。模型介绍与第三方评测均以原来源的具体版本和方法为准。