README.md

---
language:
- en
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
task_categories:
- feature-extraction
- sentence-similarity
pretty_name: GooAQ
tags:
- sentence-transformers
dataset_info:
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  splits:
  - name: train
    num_bytes: 914351688.7948598
    num_examples: 3007496
  - name: eval
    num_bytes: 760060.6025700948
    num_examples: 2500
  - name: test
    num_bytes: 760060.6025700948
    num_examples: 2500
  download_size: 613248629
  dataset_size: 915871809.9999999
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: eval
    path: data/eval-*
  - split: test
    path: data/test-*
---


# Dataset Card for GooAQ

This dataset is a collection of question-answer pairs, collected from Google. See [GooAQ](https://github.com/allenai/gooaq) for additional information.
This dataset can be used directly with Sentence Transformers to train embedding models. This dataset is equivalent to [sentence-transformers/gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq), but with 2500 evaluation samples and 2500 test samples randomly extracted from the training set.

## Dataset Subsets

### `data` subset

* Columns: "question", "answer"
* Column types: `str`, `str`
* Examples:
    ```python
    {
      'question': 'is toprol xl the same as metoprolol?',
      'answer': 'Metoprolol succinate is also known by the brand name Toprol XL. It is the extended-release form of metoprolol. Metoprolol succinate is approved to treat high blood pressure, chronic chest pain, and congestive heart failure.',
    }
    ```
* Collection strategy: Reading the GooAQ dataset from [sentence-transformers/gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq).
* Deduplified: No

### Split Details

* `train` split: 3,007,396 pairs
* `eval` split: 2,500 pairs (all unique)
* `test` split: 2,500 pairs (all unique)

There are 0 common questions across the `train`, `eval`, and `test` splits.