
# 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.
language:en region:us
{"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", "num_bytes": 5185832, "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}]}
TAGS
#language-English #region-us 

Dataset Card for "winogrande"
=============================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ 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: URL
* Repository:
* Paper:
* Point of Contact:
* 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


### Languages


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



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


### Contributions


Thanks to @thomwolf, @TevenLeScao, @patrickvonplaten, @lewtun for adding this dataset.



### 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 ### Languages


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



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 ### Contributions


Thanks to @thomwolf, @TevenLeScao, @patrickvonplaten, @lewtun for adding this dataset.
TAGS
#language-English #region-us 
 ### 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 ### Languages


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



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 ### Contributions


Thanks to @thomwolf, @TevenLeScao, @patrickvonplaten, @lewtun for adding this dataset.