language:en region:us
WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern
 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a
fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires
commonsense reasoning.
@InProceedings{ai2:winogrande,
title = {WinoGrande: An Adversarial Winograd Schema Challenge at Scale},
authors={Keisuke, Sakaguchi and Ronan, Le Bras and Chandra, Bhagavatula and Yejin, Choi
},
year={2019}
}
---
language:
- en
paperswithcode_id: winogrande
pretty_name: WinoGrande
dataset_info:
- config_name: winogrande_xs
  features:
  - name: sentence
    dtype: string
  - name: option1
    dtype: string
  - name: option2
    dtype: string
  - name: answer
    dtype: string
  splits:
  - name: train
    num_bytes: 20704
    num_examples: 160
  - name: test
    num_bytes: 227649
    num_examples: 1767
  - name: validation
    num_bytes: 164199
    num_examples: 1267
  download_size: 3395492
  dataset_size: 412552
- config_name: winogrande_s
  features:
  - name: sentence
    dtype: string
  - name: option1
    dtype: string
  - name: option2
    dtype: string
  - name: answer
    dtype: string
  splits:
  - name: train
    num_bytes: 82308
    num_examples: 640
  - name: test
    num_bytes: 227649
    num_examples: 1767
  - name: validation
    num_bytes: 164199
    num_examples: 1267
  download_size: 3395492
  dataset_size: 474156
- config_name: winogrande_m
  features:
  - name: sentence
    dtype: string
  - name: option1
    dtype: string
  - name: option2
    dtype: string
  - name: answer
    dtype: string
  splits:
  - name: train
    num_bytes: 329001
    num_examples: 2558
  - name: test
    num_bytes: 227649
    num_examples: 1767
  - name: validation
    num_bytes: 164199
    num_examples: 1267
  download_size: 3395492
  dataset_size: 720849
- config_name: winogrande_l
  features:
  - name: sentence
    dtype: string
  - name: option1
    dtype: string
  - name: option2
    dtype: string
  - name: answer
    dtype: string
  splits:
  - name: train
    num_bytes: 1319576
    num_examples: 10234
  - name: test
    num_bytes: 227649
    num_examples: 1767
  - name: validation
    num_bytes: 164199
    num_examples: 1267
  download_size: 3395492
  dataset_size: 1711424
- config_name: winogrande_xl
  features:
  - name: sentence
    dtype: string
  - name: option1
    dtype: string
  - name: option2
    dtype: string
  - name: answer
    dtype: string
  splits:
  - name: train
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    num_examples: 40398
  - name: test
    num_bytes: 227649
    num_examples: 1767
  - name: validation
    num_bytes: 164199
    num_examples: 1267
  download_size: 3395492
  dataset_size: 5577680
- config_name: winogrande_debiased
  features:
  - name: sentence
    dtype: string
  - name: option1
    dtype: string
  - name: option2
    dtype: string
  - name: answer
    dtype: string
  splits:
  - name: train
    num_bytes: 1203420
    num_examples: 9248
  - name: test
    num_bytes: 227649
    num_examples: 1767
  - name: validation
    num_bytes: 164199
    num_examples: 1267
  download_size: 3395492
  dataset_size: 1595268
---

# Dataset Card for "winogrande"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [https://leaderboard.allenai.org/winogrande/submissions/get-started](https://leaderboard.allenai.org/winogrande/submissions/get-started)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 20.37 MB
- **Size of the generated dataset:** 10.50 MB
- **Total amount of disk used:** 30.87 MB

### Dataset Summary

WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern
 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a
fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires
commonsense reasoning.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### winogrande_debiased

- **Size of downloaded dataset files:** 3.40 MB
- **Size of the generated dataset:** 1.59 MB
- **Total amount of disk used:** 4.99 MB

An example of 'train' looks as follows.
```

```

#### winogrande_l

- **Size of downloaded dataset files:** 3.40 MB
- **Size of the generated dataset:** 1.71 MB
- **Total amount of disk used:** 5.11 MB

An example of 'validation' looks as follows.
```

```

#### winogrande_m

- **Size of downloaded dataset files:** 3.40 MB
- **Size of the generated dataset:** 0.72 MB
- **Total amount of disk used:** 4.12 MB

An example of 'validation' looks as follows.
```

```

#### winogrande_s

- **Size of downloaded dataset files:** 3.40 MB
- **Size of the generated dataset:** 0.47 MB
- **Total amount of disk used:** 3.87 MB

An example of 'validation' looks as follows.
```

```

#### winogrande_xl

- **Size of downloaded dataset files:** 3.40 MB
- **Size of the generated dataset:** 5.58 MB
- **Total amount of disk used:** 8.98 MB

An example of 'train' looks as follows.
```

```

### Data Fields

The data fields are the same among all splits.

#### winogrande_debiased
- `sentence`: a `string` feature.
- `option1`: a `string` feature.
- `option2`: a `string` feature.
- `answer`: a `string` feature.

#### winogrande_l
- `sentence`: a `string` feature.
- `option1`: a `string` feature.
- `option2`: a `string` feature.
- `answer`: a `string` feature.

#### winogrande_m
- `sentence`: a `string` feature.
- `option1`: a `string` feature.
- `option2`: a `string` feature.
- `answer`: a `string` feature.

#### winogrande_s
- `sentence`: a `string` feature.
- `option1`: a `string` feature.
- `option2`: a `string` feature.
- `answer`: a `string` feature.

#### winogrande_xl
- `sentence`: a `string` feature.
- `option1`: a `string` feature.
- `option2`: a `string` feature.
- `answer`: a `string` feature.

### Data Splits

|       name        |train|validation|test|
|-------------------|----:|---------:|---:|
|winogrande_debiased| 9248|      1267|1767|
|winogrande_l       |10234|      1267|1767|
|winogrande_m       | 2558|      1267|1767|
|winogrande_s       |  640|      1267|1767|
|winogrande_xl      |40398|      1267|1767|
|winogrande_xs      |  160|      1267|1767|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@InProceedings{ai2:winogrande,
title = {WinoGrande: An Adversarial Winograd Schema Challenge at Scale},
authors={Keisuke, Sakaguchi and Ronan, Le Bras and Chandra, Bhagavatula and Yejin, Choi
},
year={2019}
}

```


### Contributions

Thanks to [@thomwolf](https://github.com/thomwolf), [@TevenLeScao](https://github.com/TevenLeScao), [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun) for adding this dataset.