language:
- tr
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
configs: null
- config_name: winogrande_debiased
data_files:
- split: train
path: winogrande_debiased/*_train-*
- split: test
path: winogrande_debiased/*_test-*
- split: validation
path: winogrande_debiased/*_validation-*
- config_name: winogrande_m
data_files:
- split: train
path: winogrande_m/winogrande_m_train-*
- split: test
path: winogrande_m/winogrande_m_test-*
- split: validation
path: winogrande_m/winogrande_m_validation-*
license: apache-2.0
Dataset Card for "winogrande"
This Dataset is part of a series of datasets aimed at advancing Turkish LLM Developments by establishing rigid Turkish benchmarks to evaluate the performance of LLM's Produced in the Turkish Language.
malhajar/winogrande-tr is a translated version of winogrande
aimed specifically to be used in the OpenLLMTurkishLeaderboard
Translated by: Mohamad Alhajar
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
aimed specifically to be used in the OpenLLMTurkishLeaderboard
Languages
Turkish
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
: astring
feature.option1
: astring
feature.option2
: astring
feature.answer
: astring
feature.
winogrande_l
sentence
: astring
feature.option1
: astring
feature.option2
: astring
feature.answer
: astring
feature.
winogrande_m
sentence
: astring
feature.option1
: astring
feature.option2
: astring
feature.answer
: astring
feature.
winogrande_s
sentence
: astring
feature.option1
: astring
feature.option2
: astring
feature.answer
: astring
feature.
winogrande_xl
sentence
: astring
feature.option1
: astring
feature.option2
: astring
feature.answer
: astring
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 |
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}
}
`