README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - text
pretty_name: 'BFHND: Big Hard Negatives Dataset (1M sample)'
size_categories:
  - 100K<n<1M
source_datasets:
  - BeIR
task_categories:
  - sentence-similarity
dataset_info:
  config_name: default
  features:
    - name: query
      dtype: string
    - name: positive
      sequence: string
    - name: negative
      sequence: string
  splits:
    - name: train
      num_bytes: 226515502
      num_examples: 1000000
train-eval-index:
  - config: default
    task: sentence-similarity
    splits:
      train_split: train
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train/*

Big Hard Negatives Dataset

A dataset for training embedding models for semantic search.

TODO: add desc

A dataset in a nixietune compatible format:

{
  "query": ")what was the immediate impact of the success of the manhattan project?",
  "pos": [
    "The presence of communication amid scientific minds was equally important to the success of the Manhattan Project as scientific intellect was. The only cloud hanging over the impressive achievement of the atomic researchers and engineers is what their success truly meant; hundreds of thousands of innocent lives obliterated."
  ],
  "neg": [
    "Abstract. The pivotal engineering and scientific success of the Twentieth century was the Manhattan Project. The Manhattan Project assimilated concepts and leaders from all scientific fields and engineering disciplines to construct the first two atomic bombs.",
    "The pivotal engineering and scientific success of the Twentieth century was the Manhattan Project. The Manhattan Project assimilated concepts and leaders from all scientific fields and engineering disciplines to construct the first two atomic bombs."
  ]
}

Usage

To use with HF datasets:

pip install datasets zstandard

from datasets import load_dataset

data = load_dataset('nixiesearch/bfhardneg-small')
print(data["train"].features)

License

Apache 2.0