reranker
Datasets
All datasets matching “reranker”ruri-dataset-reranker
Ruri-Dataset Reranker
Datasets used for training Ruri-Reranker.
Please refer to https://huggingface.co/datasets/hpprc/emb for individual datasets.
ettin-reranker-v1-data
Ettin Reranker v1 Training Data
This is the training dataset used to produce the cross-encoder/ettin-reranker-{17m,32m,68m,150m,400m,1b}-v1 family of CrossEncoder rerankers. It's a mix of broad-domain text-pair data and retrieval pairs rescored with a strong teacher reranker, with every label produced by an automated scoring system rather than a human annotator.
Structure
Every config has the same three columns:
column
type
description
query
string
The… See the full description on the dataset page: https://huggingface.co/datasets/cross-encoder/ettin-reranker-v1-data.mmarco-hard-negatives-reranker-filtered
mMARCO Reranker-Filtered Hard Negatives (Multilingual)
Overview
This dataset is built from mMARCO (multilingual MS MARCO) triplets for each language subset. For each (query, positive), hard negatives are bundled and then filtered using cross-encoder re-scoring. The goal is to remove negatives that are too strong or incorrect for training. The same procedure is applied to all language subsets.
The dataset is published as mmarco-hard-negatives-reranker-filtered with… See the full description on the dataset page: https://huggingface.co/datasets/hotchpotch/mmarco-hard-negatives-reranker-filtered.reranker-scores
Reranker-Scores
既存の日本語検索・QAデータセットについて、データセット中のクエリに付与された正・負例の関連度を多言語・日本語reranker 5種類を用いてスコア付けしたデータセットです。クエリごとに200件程度の正・負例文書が付与されています (事例ごとに付与個数はバラバラなのでご注意ください)。score.pos.avg および score.neg.avg はそれぞれ正例・負例についての5種のrerankerの平均スコアになっています。
Short Name
Hub ID
bge
BAAI/bge-reranker-v2-m3
gte
Alibaba-NLP/gte-multilingual-reranker-base
ruri
cl-nagoya/ruri-reranker-large
ruriv3-preview
cl-nagoya/ruri-v3-reranker-310m-preview
ja-ce… See the full description on the dataset page: https://huggingface.co/datasets/hpprc/reranker-scores.KaLM-reranker-training-data
Lychee-KaLM-Reranker Training Data
A large-scale, ready-to-use multilingual dataset for fine-tuning reranking models.
This repository contains 3,885,265 training samples collected from 54 datasets, covering English, Chinese, and multilingual retrieval tasks. Each sample includes task instructions, positive passages, at least 16 hard negatives, and teacher scores annotated by Qwen3-Reranker-8B.
When expanded into point-wise query–passage pairs, the dataset provides at least 66… See the full description on the dataset page: https://huggingface.co/datasets/KaLM-Embedding/KaLM-reranker-training-data.relevance-reranker-v3