NanoFEVER-bm25 / README.md
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---
dataset_info:
- config_name: corpus
features:
- name: _id
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 6285894
num_examples: 4996
download_size: 3917948
dataset_size: 6285894
- config_name: queries
features:
- name: _id
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 2948
num_examples: 50
download_size: 3678
dataset_size: 2948
- config_name: relevance
features:
- name: query-id
dtype: string
- name: positive-corpus-ids
sequence: string
- name: bm25-ranked-ids
sequence: string
splits:
- name: train
num_bytes: 5924663
num_examples: 50
download_size: 489932
dataset_size: 5924663
configs:
- config_name: corpus
data_files:
- split: train
path: corpus/train-*
- config_name: queries
data_files:
- split: train
path: queries/train-*
- config_name: relevance
data_files:
- split: train
path: relevance/train-*
language:
- en
tags:
- sentence-transformers
size_categories:
- 1K<n<10K
---
# NanoBEIR FEVER with BM25 rankings
This dataset is an updated variant of [NanoFEVER](https://huggingface.co/datasets/zeta-alpha-ai/NanoFEVER), which is a subset of the FEVER dataset from the Benchmark for Information Retrieval (BEIR).
FEVER was created as a subset of the rather large BEIR, designed to be more efficient to run. This dataset adds a `bm25-ranked-ids` column to the `relevance` subset, which contains a ranking of every single passage in the corpus to the query.
This dataset is used in Sentence Transformers for evaluating CrossEncoder (i.e. reranker) models on NanoBEIR by reranking the top *k* results from BM25.