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  1. .gitattributes +27 -0
  2. README.md +365 -0
  3. dataset_infos.json +1 -0
  4. winogrande.py +145 -0
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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ paperswithcode_id: winogrande
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+ pretty_name: WinoGrande
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+ dataset_info:
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+ - config_name: winogrande_xs
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+ dataset_size: 1711424
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+ - config_name: winogrande_xl
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+ features:
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+ - name: sentence
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+ num_examples: 1267
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+ download_size: 3395492
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+ dataset_size: 5577680
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+ - config_name: winogrande_debiased
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+ features:
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+ - name: sentence
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+ dtype: string
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+ - name: option1
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+ dtype: string
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+ - name: option2
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+ dtype: string
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+ - name: answer
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+ dtype: string
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+ splits:
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+ - name: train
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+ - name: test
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+ num_bytes: 227649
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+ num_examples: 1767
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+ - name: validation
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+ num_bytes: 164199
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+ num_examples: 1267
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+ download_size: 3395492
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+ dataset_size: 1595268
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+ ---
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+
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+ # Dataset Card for "winogrande"
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+ - [Contributions](#contributions)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** [https://leaderboard.allenai.org/winogrande/submissions/get-started](https://leaderboard.allenai.org/winogrande/submissions/get-started)
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+ - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+ - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+ - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+ - **Size of downloaded dataset files:** 20.37 MB
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+ - **Size of the generated dataset:** 10.50 MB
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+ - **Total amount of disk used:** 30.87 MB
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+
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+ ### Dataset Summary
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+
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+ WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern
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+ 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a
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+ fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires
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+ commonsense reasoning.
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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+ ### Languages
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ #### winogrande_debiased
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+
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+ - **Size of downloaded dataset files:** 3.40 MB
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+ - **Size of the generated dataset:** 1.59 MB
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+ - **Total amount of disk used:** 4.99 MB
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+
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+ An example of 'train' looks as follows.
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+ ```
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+
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+ ```
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+
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+ #### winogrande_l
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+
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+ - **Size of downloaded dataset files:** 3.40 MB
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+ - **Size of the generated dataset:** 1.71 MB
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+ - **Total amount of disk used:** 5.11 MB
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+
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+ An example of 'validation' looks as follows.
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+ ```
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+
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+ ```
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+
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+ #### winogrande_m
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+
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+ - **Size of downloaded dataset files:** 3.40 MB
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+ - **Size of the generated dataset:** 0.72 MB
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+ - **Total amount of disk used:** 4.12 MB
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+
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+ An example of 'validation' looks as follows.
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+ ```
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+
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+ ```
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+
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+ #### winogrande_s
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+
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+ - **Size of downloaded dataset files:** 3.40 MB
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+ - **Size of the generated dataset:** 0.47 MB
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+ - **Total amount of disk used:** 3.87 MB
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+
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+ An example of 'validation' looks as follows.
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+ ```
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+
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+ ```
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+
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+ #### winogrande_xl
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+
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+ - **Size of downloaded dataset files:** 3.40 MB
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+ - **Size of the generated dataset:** 5.58 MB
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+ - **Total amount of disk used:** 8.98 MB
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+
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+ An example of 'train' looks as follows.
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+ ```
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+
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+ ```
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+
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+ ### Data Fields
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+
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+ The data fields are the same among all splits.
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+
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+ #### winogrande_debiased
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+ - `sentence`: a `string` feature.
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+ - `option1`: a `string` feature.
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+ - `option2`: a `string` feature.
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+ - `answer`: a `string` feature.
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+
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+ #### winogrande_l
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+ - `sentence`: a `string` feature.
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+ - `option1`: a `string` feature.
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+ - `option2`: a `string` feature.
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+ - `answer`: a `string` feature.
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+
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+ #### winogrande_m
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+ - `sentence`: a `string` feature.
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+ - `option1`: a `string` feature.
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+ - `option2`: a `string` feature.
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+ - `answer`: a `string` feature.
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+
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+ #### winogrande_s
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+ - `sentence`: a `string` feature.
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+ - `option1`: a `string` feature.
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+ - `option2`: a `string` feature.
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+ - `answer`: a `string` feature.
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+
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+ #### winogrande_xl
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+ - `sentence`: a `string` feature.
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+ - `option1`: a `string` feature.
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+ - `option2`: a `string` feature.
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+ - `answer`: a `string` feature.
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+
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+ ### Data Splits
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+
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+ | name |train|validation|test|
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+ |-------------------|----:|---------:|---:|
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+ |winogrande_debiased| 9248| 1267|1767|
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+ |winogrande_l |10234| 1267|1767|
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+ |winogrande_m | 2558| 1267|1767|
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+ |winogrande_s | 640| 1267|1767|
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+ |winogrande_xl |40398| 1267|1767|
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+ |winogrande_xs | 160| 1267|1767|
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+
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+ ## Dataset Creation
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+
298
+ ### Curation Rationale
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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+ #### Who are the source language producers?
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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+ ### Annotations
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+
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+ #### Annotation process
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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+
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+ #### Who are the annotators?
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+
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+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
321
+
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+ ### Personal and Sensitive Information
323
+
324
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
325
+
326
+ ## Considerations for Using the Data
327
+
328
+ ### Social Impact of Dataset
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+
330
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
331
+
332
+ ### Discussion of Biases
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+
334
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
335
+
336
+ ### Other Known Limitations
337
+
338
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
339
+
340
+ ## Additional Information
341
+
342
+ ### Dataset Curators
343
+
344
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
345
+
346
+ ### Licensing Information
347
+
348
+ [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
349
+
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+ ### Citation Information
351
+
352
+ ```
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+ @InProceedings{ai2:winogrande,
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+ title = {WinoGrande: An Adversarial Winograd Schema Challenge at Scale},
355
+ authors={Keisuke, Sakaguchi and Ronan, Le Bras and Chandra, Bhagavatula and Yejin, Choi
356
+ },
357
+ year={2019}
358
+ }
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+
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+ ```
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+
362
+
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+ ### Contributions
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+
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+ 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.
dataset_infos.json ADDED
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Formulated as a\nfill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires\ncommonsense reasoning.\n", "citation": "@InProceedings{ai2:winogrande,\ntitle = {WinoGrande: An Adversarial Winograd Schema Challenge at Scale},\nauthors={Keisuke, Sakaguchi and Ronan, Le Bras and Chandra, Bhagavatula and Yejin, Choi\n},\nyear={2019}\n}\n", "homepage": "https://leaderboard.allenai.org/winogrande/submissions/get-started", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "option1": {"dtype": "string", "id": null, "_type": "Value"}, "option2": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "winogrande", "config_name": "winogrande_l", "version": {"version_str": "1.1.0", "description": "", "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1319576, "num_examples": 10234, "dataset_name": "winogrande"}, "test": {"name": "test", "num_bytes": 227649, "num_examples": 1767, "dataset_name": "winogrande"}, "validation": {"name": "validation", "num_bytes": 164199, "num_examples": 1267, "dataset_name": "winogrande"}}, "download_checksums": {"https://storage.googleapis.com/ai2-mosaic/public/winogrande/winogrande_1.1.zip": {"num_bytes": 3395492, "checksum": "3619ab104d8be2977b25c90ff420cb42d491707dcc75362a1e5d22bc082b7318"}}, "download_size": 3395492, "post_processing_size": null, "dataset_size": 1711424, "size_in_bytes": 5106916}, "winogrande_xl": {"description": "WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern\n 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. 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winogrande.py ADDED
@@ -0,0 +1,145 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """TODO(winogrande): Add a description here."""
2
+
3
+
4
+ import json
5
+ import os
6
+
7
+ import datasets
8
+
9
+
10
+ # TODO(winogrande): BibTeX citation
11
+ _CITATION = """\
12
+ @InProceedings{ai2:winogrande,
13
+ title = {WinoGrande: An Adversarial Winograd Schema Challenge at Scale},
14
+ authors={Keisuke, Sakaguchi and Ronan, Le Bras and Chandra, Bhagavatula and Yejin, Choi
15
+ },
16
+ year={2019}
17
+ }
18
+ """
19
+
20
+ # TODO(winogrande):
21
+ _DESCRIPTION = """\
22
+ WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern
23
+ 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a
24
+ fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires
25
+ commonsense reasoning.
26
+ """
27
+
28
+ _URL = "https://storage.googleapis.com/ai2-mosaic/public/winogrande/winogrande_1.1.zip"
29
+ _FORMATS = ["xs", "s", "m", "l", "xl", "debiased"]
30
+
31
+
32
+ class WinograndeConfig(datasets.BuilderConfig):
33
+
34
+ """BuilderConfig for Discofuse"""
35
+
36
+ def __init__(self, data_size, **kwargs):
37
+ """
38
+
39
+ Args:
40
+ data_size: the format of the training set we want to use (xs, s, m, l, xl, debiased)
41
+ **kwargs: keyword arguments forwarded to super.
42
+ """
43
+ super(WinograndeConfig, self).__init__(version=datasets.Version("1.1.0", ""), **kwargs)
44
+ self.data_size = data_size
45
+
46
+
47
+ class Winogrande(datasets.GeneratorBasedBuilder):
48
+ """TODO(winogrande): Short description of my dataset."""
49
+
50
+ # TODO(winogrande): Set up version.
51
+ VERSION = datasets.Version("1.1.0")
52
+ BUILDER_CONFIGS = [
53
+ WinograndeConfig(name="winogrande_" + data_size, description="AI2 dataset", data_size=data_size)
54
+ for data_size in _FORMATS
55
+ ]
56
+
57
+ def _info(self):
58
+ # TODO(winogrande): Specifies the datasets.DatasetInfo object
59
+ return datasets.DatasetInfo(
60
+ # This is the description that will appear on the datasets page.
61
+ description=_DESCRIPTION,
62
+ # datasets.features.FeatureConnectors
63
+ features=datasets.Features(
64
+ {
65
+ "sentence": datasets.Value("string"),
66
+ "option1": datasets.Value("string"),
67
+ "option2": datasets.Value("string"),
68
+ "answer": datasets.Value("string")
69
+ # These are the features of your dataset like images, labels ...
70
+ }
71
+ ),
72
+ # If there's a common (input, target) tuple from the features,
73
+ # specify them here. They'll be used if as_supervised=True in
74
+ # builder.as_dataset.
75
+ supervised_keys=None,
76
+ # Homepage of the dataset for documentation
77
+ homepage="https://leaderboard.allenai.org/winogrande/submissions/get-started",
78
+ citation=_CITATION,
79
+ )
80
+
81
+ def _split_generators(self, dl_manager):
82
+ """Returns SplitGenerators."""
83
+ # TODO(winogrande): Downloads the data and defines the splits
84
+ # dl_manager is a datasets.download.DownloadManager that can be used to
85
+ # download and extract URLs
86
+ dl_dir = dl_manager.download_and_extract(_URL)
87
+ data_dir = os.path.join(dl_dir, "winogrande_1.1")
88
+ return [
89
+ datasets.SplitGenerator(
90
+ name=datasets.Split.TRAIN,
91
+ # These kwargs will be passed to _generate_examples
92
+ gen_kwargs={
93
+ "filepath": os.path.join(data_dir, f"train_{self.config.data_size}.jsonl"),
94
+ # 'labelpath': os.path.join(data_dir, 'train_{}-labels.lst'.format(self.config.data_size)),
95
+ "split": "train",
96
+ },
97
+ ),
98
+ datasets.SplitGenerator(
99
+ name=datasets.Split.TEST,
100
+ # These kwargs will be passed to _generate_examples
101
+ gen_kwargs={"filepath": os.path.join(data_dir, "test.jsonl"), "split": "test"},
102
+ ),
103
+ datasets.SplitGenerator(
104
+ name=datasets.Split.VALIDATION,
105
+ # These kwargs will be passed to _generate_examples
106
+ gen_kwargs={
107
+ "filepath": os.path.join(data_dir, "dev.jsonl"),
108
+ # 'labelpath': os.path.join(data_dir, 'dev-labels.lst'),
109
+ "split": "dev",
110
+ },
111
+ ),
112
+ ]
113
+
114
+ def _generate_examples(self, filepath, split):
115
+ """Yields examples."""
116
+ # TODO(winogrande): Yields (key, example) tuples from the dataset
117
+ with open(filepath, encoding="utf-8") as f:
118
+ for id_, row in enumerate(f):
119
+ data = json.loads(row)
120
+ if split == "test":
121
+ yield id_, {
122
+ "sentence": data["sentence"],
123
+ "option1": data["option1"],
124
+ "option2": data["option2"],
125
+ "answer": "",
126
+ }
127
+ else:
128
+ yield id_, {
129
+ "sentence": data["sentence"],
130
+ "option1": data["option1"],
131
+ "option2": data["option2"],
132
+ "answer": data["answer"],
133
+ }
134
+
135
+
136
+ # def _generate_test_example(filepath, split, labelpath=None):
137
+ # with open(filepath, encoding="utf-8") as f:
138
+ # for id_, row in enumerate(f):
139
+ # data = json.loads(row)
140
+ # yield id_,{
141
+ # 'sentence': data['sentence'],
142
+ # 'option1': data['option1'],
143
+ # 'option2': data['option2'],
144
+ # 'answer': None
145
+ # }