--- language: - en paperswithcode_id: xnli pretty_name: Cross-lingual Natural Language Inference dataset_info: - config_name: ar features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 107399934 num_examples: 392702 - name: test num_bytes: 1294561 num_examples: 5010 - name: validation num_bytes: 633009 num_examples: 2490 download_size: 483963712 dataset_size: 109327504 - config_name: bg features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 125973545 num_examples: 392702 - name: test num_bytes: 1573042 num_examples: 5010 - name: validation num_bytes: 774069 num_examples: 2490 download_size: 483963712 dataset_size: 128320656 - config_name: de features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 84684460 num_examples: 392702 - name: test num_bytes: 996496 num_examples: 5010 - name: validation num_bytes: 494612 num_examples: 2490 download_size: 483963712 dataset_size: 86175568 - config_name: el features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 139753678 num_examples: 392702 - name: test num_bytes: 1704793 num_examples: 5010 - name: validation num_bytes: 841234 num_examples: 2490 download_size: 483963712 dataset_size: 142299705 - config_name: en features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 74444346 num_examples: 392702 - name: test num_bytes: 875142 num_examples: 5010 - name: validation num_bytes: 433471 num_examples: 2490 download_size: 483963712 dataset_size: 75752959 - config_name: es features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 81383604 num_examples: 392702 - name: test num_bytes: 969821 num_examples: 5010 - name: validation num_bytes: 478430 num_examples: 2490 download_size: 483963712 dataset_size: 82831855 - config_name: fr features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 85809099 num_examples: 392702 - name: test num_bytes: 1029247 num_examples: 5010 - name: validation num_bytes: 510112 num_examples: 2490 download_size: 483963712 dataset_size: 87348458 - config_name: hi features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 170594284 num_examples: 392702 - name: test num_bytes: 2073081 num_examples: 5010 - name: validation num_bytes: 1023923 num_examples: 2490 download_size: 483963712 dataset_size: 173691288 - config_name: ru features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 129859935 num_examples: 392702 - name: test num_bytes: 1603474 num_examples: 5010 - name: validation num_bytes: 786450 num_examples: 2490 download_size: 483963712 dataset_size: 132249859 - config_name: sw features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 69286045 num_examples: 392702 - name: test num_bytes: 871659 num_examples: 5010 - name: validation num_bytes: 429858 num_examples: 2490 download_size: 483963712 dataset_size: 70587562 - config_name: th features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 176063212 num_examples: 392702 - name: test num_bytes: 2147023 num_examples: 5010 - name: validation num_bytes: 1061168 num_examples: 2490 download_size: 483963712 dataset_size: 179271403 - config_name: tr features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 71637460 num_examples: 392702 - name: test num_bytes: 934942 num_examples: 5010 - name: validation num_bytes: 459316 num_examples: 2490 download_size: 483963712 dataset_size: 73031718 - config_name: ur features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 96441806 num_examples: 392702 - name: test num_bytes: 1416249 num_examples: 5010 - name: validation num_bytes: 699960 num_examples: 2490 download_size: 483963712 dataset_size: 98558015 - config_name: vi features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 101417750 num_examples: 392702 - name: test num_bytes: 1190225 num_examples: 5010 - name: validation num_bytes: 590688 num_examples: 2490 download_size: 483963712 dataset_size: 103198663 - config_name: zh features: - name: premise dtype: string - name: hypothesis dtype: string - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 72225161 num_examples: 392702 - name: test num_bytes: 777937 num_examples: 5010 - name: validation num_bytes: 384859 num_examples: 2490 download_size: 483963712 dataset_size: 73387957 - config_name: all_languages features: - name: premise dtype: translation: languages: - ar - bg - de - el - en - es - fr - hi - ru - sw - th - tr - ur - vi - zh - name: hypothesis dtype: translation_variable_languages: languages: - ar - bg - de - el - en - es - fr - hi - ru - sw - th - tr - ur - vi - zh num_languages: 15 - name: label dtype: class_label: names: 0: entailment 1: neutral 2: contradiction splits: - name: train num_bytes: 1581474731 num_examples: 392702 - name: test num_bytes: 19387508 num_examples: 5010 - name: validation num_bytes: 9566255 num_examples: 2490 download_size: 483963712 dataset_size: 1610428494 --- # Dataset Card for "xnli" ## 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://www.nyu.edu/projects/bowman/xnli/](https://www.nyu.edu/projects/bowman/xnli/) - **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:** 7384.70 MB - **Size of the generated dataset:** 3076.99 MB - **Total amount of disk used:** 10461.69 MB ### Dataset Summary XNLI is a subset of a few thousand examples from MNLI which has been translated into a 14 different languages (some low-ish resource). As with MNLI, the goal is to predict textual entailment (does sentence A imply/contradict/neither sentence B) and is a classification task (given two sentences, predict one of three labels). ### 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 #### all_languages - **Size of downloaded dataset files:** 461.54 MB - **Size of the generated dataset:** 1535.82 MB - **Total amount of disk used:** 1997.37 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "hypothesis": "{\"language\": [\"ar\", \"bg\", \"de\", \"el\", \"en\", \"es\", \"fr\", \"hi\", \"ru\", \"sw\", \"th\", \"tr\", \"ur\", \"vi\", \"zh\"], \"translation\": [\"احد اع...", "label": 0, "premise": "{\"ar\": \"واحدة من رقابنا ستقوم بتنفيذ تعليماتك كلها بكل دقة\", \"bg\": \"един от нашите номера ще ви даде инструкции .\", \"de\": \"Eine ..." } ``` #### ar - **Size of downloaded dataset files:** 461.54 MB - **Size of the generated dataset:** 104.26 MB - **Total amount of disk used:** 565.81 MB An example of 'validation' looks as follows. ``` { "hypothesis": "اتصل بأمه حالما أوصلته حافلة المدرسية.", "label": 1, "premise": "وقال، ماما، لقد عدت للمنزل." } ``` #### bg - **Size of downloaded dataset files:** 461.54 MB - **Size of the generated dataset:** 122.38 MB - **Total amount of disk used:** 583.92 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "hypothesis": "\"губиш нещата на следното ниво , ако хората си припомнят .\"...", "label": 0, "premise": "\"по време на сезона и предполагам , че на твоето ниво ще ги загубиш на следващото ниво , ако те решат да си припомнят отбора на ..." } ``` #### de - **Size of downloaded dataset files:** 461.54 MB - **Size of the generated dataset:** 82.18 MB - **Total amount of disk used:** 543.73 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "hypothesis": "Man verliert die Dinge auf die folgende Ebene , wenn sich die Leute erinnern .", "label": 0, "premise": "\"Du weißt , während der Saison und ich schätze , auf deiner Ebene verlierst du sie auf die nächste Ebene , wenn sie sich entschl..." } ``` #### el - **Size of downloaded dataset files:** 461.54 MB - **Size of the generated dataset:** 135.71 MB - **Total amount of disk used:** 597.25 MB An example of 'validation' looks as follows. ``` This example was too long and was cropped: { "hypothesis": "\"Τηλεφώνησε στη μαμά του μόλις το σχολικό λεωφορείο τον άφησε.\"...", "label": 1, "premise": "Και είπε, Μαμά, έφτασα στο σπίτι." } ``` ### Data Fields The data fields are the same among all splits. #### all_languages - `premise`: a multilingual `string` variable, with possible languages including `ar`, `bg`, `de`, `el`, `en`. - `hypothesis`: a multilingual `string` variable, with possible languages including `ar`, `bg`, `de`, `el`, `en`. - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). #### ar - `premise`: a `string` feature. - `hypothesis`: a `string` feature. - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). #### bg - `premise`: a `string` feature. - `hypothesis`: a `string` feature. - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). #### de - `premise`: a `string` feature. - `hypothesis`: a `string` feature. - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). #### el - `premise`: a `string` feature. - `hypothesis`: a `string` feature. - `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2). ### Data Splits | name |train |validation|test| |-------------|-----:|---------:|---:| |all_languages|392702| 2490|5010| |ar |392702| 2490|5010| |bg |392702| 2490|5010| |de |392702| 2490|5010| |el |392702| 2490|5010| ## 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{conneau2018xnli, author = {Conneau, Alexis and Rinott, Ruty and Lample, Guillaume and Williams, Adina and Bowman, Samuel R. and Schwenk, Holger and Stoyanov, Veselin}, title = {XNLI: Evaluating Cross-lingual Sentence Representations}, booktitle = {Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing}, year = {2018}, publisher = {Association for Computational Linguistics}, location = {Brussels, Belgium}, } ``` ### Contributions Thanks to [@lewtun](https://github.com/lewtun), [@mariamabarham](https://github.com/mariamabarham), [@thomwolf](https://github.com/thomwolf), [@lhoestq](https://github.com/lhoestq), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.