albertvillanova
HF staff
Convert dataset sizes from base 2 to base 10 in the dataset card (#6)
0b7f5e3
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - crowdsourced | |
| - found | |
| language: | |
| - fr | |
| license: | |
| - cc-by-nc-sa-3.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - question-answering | |
| - text-retrieval | |
| task_ids: | |
| - extractive-qa | |
| - closed-domain-qa | |
| paperswithcode_id: fquad | |
| pretty_name: 'FQuAD: French Question Answering Dataset' | |
| dataset_info: | |
| features: | |
| - name: context | |
| dtype: string | |
| - name: questions | |
| sequence: string | |
| - name: answers | |
| sequence: | |
| - name: texts | |
| dtype: string | |
| - name: answers_starts | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 5898752 | |
| num_examples: 4921 | |
| - name: validation | |
| num_bytes: 1031456 | |
| num_examples: 768 | |
| download_size: 0 | |
| dataset_size: 6930208 | |
| # Dataset Card for FQuAD | |
| ## 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://fquad.illuin.tech/](https://fquad.illuin.tech/) | |
| - **Paper:** [FQuAD: French Question Answering Dataset](https://arxiv.org/abs/2002.06071) | |
| - **Point of Contact:** [https://www.illuin.tech/contact/](https://www.illuin.tech/contact/) | |
| - **Size of downloaded dataset files:** 3.29 MB | |
| - **Size of the generated dataset:** 6.94 MB | |
| - **Total amount of disk used:** 10.23 MB | |
| ### Dataset Summary | |
| FQuAD: French Question Answering Dataset | |
| We introduce FQuAD, a native French Question Answering Dataset. | |
| FQuAD contains 25,000+ question and answer pairs. | |
| Finetuning CamemBERT on FQuAD yields a F1 score of 88% and an exact match of 77.9%. | |
| Developped to provide a SQuAD equivalent in the French language. Questions are original and based on high quality Wikipedia articles. | |
| Please, note this dataset is licensed for non-commercial purposes and users must agree to the following terms and conditions: | |
| 1. Use FQuAD only for internal research purposes. | |
| 2. Not make any copy except a safety one. | |
| 3. Not redistribute it (or part of it) in any way, even for free. | |
| 4. Not sell it or use it for any commercial purpose. Contact us for a possible commercial licence. | |
| 5. Mention the corpus origin and Illuin Technology in all publications about experiments using FQuAD. | |
| 6. Redistribute to Illuin Technology any improved or enriched version you could make of that corpus. | |
| Request manually download of the data from: https://fquad.illuin.tech/ | |
| ### Supported Tasks and Leaderboards | |
| - `closed-domain-qa`, `text-retrieval`: This dataset is intended to be used for `closed-domain-qa`, but can also be used for information retrieval tasks. | |
| ### Languages | |
| This dataset is exclusively in French, with context data from Wikipedia and questions from French university students (`fr`). | |
| ## Dataset Structure | |
| ### Data Instances | |
| #### default | |
| - **Size of downloaded dataset files:** 3.29 MB | |
| - **Size of the generated dataset:** 6.94 MB | |
| - **Total amount of disk used:** 10.23 MB | |
| An example of 'validation' looks as follows. | |
| ``` | |
| This example was too long and was cropped: | |
| { | |
| "answers": { | |
| "answers_starts": [161, 46, 204], | |
| "texts": ["La Vierge aux rochers", "documents contemporains", "objets de spéculations"] | |
| }, | |
| "context": "\"Les deux tableaux sont certes décrits par des documents contemporains à leur création mais ceux-ci ne le font qu'indirectement ...", | |
| "questions": ["Que concerne principalement les documents ?", "Par quoi sont décrit les deux tableaux ?", "Quels types d'objets sont les deux tableaux aux yeux des chercheurs ?"] | |
| } | |
| ``` | |
| ### Data Fields | |
| The data fields are the same among all splits. | |
| #### default | |
| - `context`: a `string` feature. | |
| - `questions`: a `list` of `string` features. | |
| - `answers`: a dictionary feature containing: | |
| - `texts`: a `string` feature. | |
| - `answers_starts`: a `int32` feature. | |
| ### Data Splits | |
| The FQuAD dataset has 3 splits: _train_, _validation_, and _test_. The _test_ split is however not released publicly at the moment. The splits contain disjoint sets of articles. The following table contains stats about each split. | |
| Dataset Split | Number of Articles in Split | Number of paragraphs in split | Number of questions in split | |
| --------------|------------------------------|--------------------------|------------------------- | |
| Train | 117 | 4921 | 20731 | |
| Validation | 768 | 51.0% | 3188 | |
| Test | 10 | 532 | 2189 | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| The FQuAD dataset was created by Illuin technology. It was developped to provide a SQuAD equivalent in the French language. Questions are original and based on high quality Wikipedia articles. | |
| ### Source Data | |
| The text used for the contexts are from the curated list of French High-Quality Wikipedia [articles](https://fr.wikipedia.org/wiki/Cat%C3%A9gorie:Article_de_qualit%C3%A9). | |
| ### Annotations | |
| Annotations (spans and questions) are written by students of the CentraleSupélec school of engineering. | |
| Wikipedia articles were scraped and Illuin used an internally-developped tool to help annotators ask questions and indicate the answer spans. | |
| Annotators were given paragraph sized contexts and asked to generate 4/5 non-trivial questions about information in the context. | |
| ### Personal and Sensitive Information | |
| No personal or sensitive information is included in this dataset. This has been manually verified by the dataset curators. | |
| ## Considerations for Using the Data | |
| Users should consider this dataset is sampled from Wikipedia data which might not be representative of all QA use cases. | |
| ### Social Impact of Dataset | |
| The social biases of this dataset have not yet been investigated. | |
| ### Discussion of Biases | |
| The social biases of this dataset have not yet been investigated, though articles have been selected by their quality and objectivity. | |
| ### Other Known Limitations | |
| The limitations of the FQuAD dataset have not yet been investigated. | |
| ## Additional Information | |
| ### Dataset Curators | |
| Illuin Technology: [https://fquad.illuin.tech/](https://fquad.illuin.tech/) | |
| ### Licensing Information | |
| The FQuAD dataset is licensed under the [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/fr/) license. | |
| It allows personal and academic research uses of the dataset, but not commercial uses. So concretely, the dataset cannot be used to train a model that is then put into production within a business or a company. For this type of commercial use, we invite FQuAD users to contact [the authors](https://www.illuin.tech/contact/) to discuss possible partnerships. | |
| ### Citation Information | |
| ``` | |
| @ARTICLE{2020arXiv200206071 | |
| author = {Martin, d'Hoffschmidt and Maxime, Vidal and | |
| Wacim, Belblidia and Tom, Brendlé}, | |
| title = "{FQuAD: French Question Answering Dataset}", | |
| journal = {arXiv e-prints}, | |
| keywords = {Computer Science - Computation and Language}, | |
| year = "2020", | |
| month = "Feb", | |
| eid = {arXiv:2002.06071}, | |
| pages = {arXiv:2002.06071}, | |
| archivePrefix = {arXiv}, | |
| eprint = {2002.06071}, | |
| primaryClass = {cs.CL} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@thomwolf](https://github.com/thomwolf), [@mariamabarham](https://github.com/mariamabarham), [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@albertvillanova](https://github.com/albertvillanova) for adding this dataset. | |
| Thanks to [@ManuelFay](https://github.com/manuelfay) for providing information on the dataset creation process. |