# squad by Pranav R: AI Training Dataset
Source: https://savrn.com/datasets/squad
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Dataset Card

By Pranav R, published under cc-by-sa-4.0, revision 7b6d24c440a3.

### Dataset Card for SQuAD

### Table of Contents

- Dataset Card for "squad"
- Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - plain_text
  - Data Fields
  - plain_text
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Initial Data Collection and Normalization
  - Who are the source language producers?
  - Annotations
  - Annotation process
  - Who are the annotators?
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

### Dataset Description

- Homepage: https://rajpurkar.github.io/SQuAD-explorer/
- Repository: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- Paper: https://arxiv.org/abs/1606.05250
- Point of Contact: [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Dataset Summary

Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.

SQuAD 1.1 contains 100,000+ question-answer pairs on 500+ articles.

[Read the full dataset card (469 words)](https://savrn.com/datasets/squad/card)

## Structure

### plain_text 98,169 rows

| Split | Rows | Size |
| --- | --- | --- |
| train | 87,599 | 25.0 MB |
| validation | 10,570 | 3.2 MB |

idstringtitlestringcontextstringquestionstringanswersvalue

## Details

Repository

rajpurkar/squad

Publisher

Pranav R

Task category

Question answering

Tags

Not stated by the source

Size category

10K<n<100K

Languages

en

Revision

7b6d24c440a36b6815f21b70d25016731768db1f

Last updated

2024-03-04

## SAVRN's Notes on squad

SQuAD is 98,169 crowd-written question-answer pairs posed over Wikipedia articles, 16.3 MB under CC BY-SA 4.0, published here by Pranav Rajpurkar and last touched in March 2024. It remains the archetypal extractive-QA fine-tuning target: every answer is a span of the source passage, so the task reduces to boundary selection rather than generation. The inbound list on our page makes the usage pattern explicit — bert-base-cased-squad-extractive-qa, bert-base-squad-qa and similar BERT-era extractive models all disclose training on it.

CC BY-SA 4.0 means attribution plus share-alike on adapted material — workable for research, but clear it before a commercial deployment builds on a SQuAD fine-tune. Two practical warnings. Every answer is a span of a Wikipedia passage, so any model pretrained heavily on Wikipedia has seen the context; and the benchmark has been saturated since the BERT era, so expect ceiling-level scores that no longer discriminate between systems. Use it to validate an extractive-QA pipeline, not to prove capability.

SAVRN Research

## Files

4 files, 16.3 MB in total.

Data2 files · 16.3 MB

Documentation1 file · 7.6 KB

Repository1 file · 1.2 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| plain_text/train-00000-of-00001.parquet | Data | 14.5 MB | ea7f52bac024 |
| plain_text/validation-00000-of-00001.parquet | Data | 1.8 MB | 8c6646d36bd5 |
| README.md | Documentation | 7.6 KB | — |
| .gitattributes | Repository | 1.2 KB | — |

## License and Download

License

cc-by-sa-4.0

Access

No access gate

[Download from Pranav R](https://huggingface.co/datasets/rajpurkar/squad)

Released by Pranav R through its official repository on Hugging Face. [Read the license](https://creativecommons.org/licenses/by-sa/4.0/).

## Models Trained on This Dataset

- Trained on (disclosed)[bert-base-cased-squad-extractive-qa](https://savrn.com/models/bert-base-cased-squad-extractive-qa)
- Trained on (disclosed)[Extractive-QA_BERT_body](https://savrn.com/models/extractive-qa-bert-body)
- Trained on (disclosed)[bert-base-squad-qa](https://savrn.com/models/bert-base-squad-qa)

## Pranav R

[All models and datasets](https://savrn.com/model-publishers/rajpurkar)

## Explore More

- [The dataset directory](https://savrn.com/datasets)
- [The model directory](https://savrn.com/models)
- [Research papers](https://savrn.com/papers)

## Source

- Repository metadata, read 2026-10-19.
- [Hugging Face record](https://huggingface.co/datasets/rajpurkar/squad)
- [How the hub is built](https://savrn.com/model-hub/methodology)