

# Dataset Card for "squad_fr"
## 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)
## Dataset Description
- **Paper:**  [On the Usability of Transformers-based models for a French Question-Answering task](https://hal.archives-ouvertes.fr/hal-03336060)
- **Size of downloaded dataset files:** 10 MB
- **Size of the generated dataset:** 73 MB
- **Total amount of disk used:** 83 MB
### Dataset Summary
SQuAD-fr:
- a translated version of the Stanford Question Answering Dataset (SQuAD) into French
  - obtained through automatic translation of the English dataset
- a reading comprehension dataset, consisting of approximately 90K factoid questions on Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage
- serves as a means of data augmentation on FQuAD and PIAF benchmarks
### 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.
## Dataset Structure
### Data Instances
#### default
- **Size of downloaded dataset files:** 10 MB
- **Size of the generated dataset:** 73 MB
- **Total amount of disk used:** 83 MB
An example of 'train' looks as follows.
```
{
    "answers": {
        "answer_start": [1],
        "text": ["This is a test text"]
    },
    "context": "This is a test context.",
    "id": "1",
    "question": "Is this a test?",
    "title": "train test"
}
```
### Data Fields
The data fields are the same among all splits.
#### plain_text
- `id`: a `string` feature.
- `title`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `answer_start`: a `int32` feature.

### Data Splits
|   name   |train|validation|
|----------|----:|---------:|
|1.1.0|87514|     17492|
## Dataset Creation
### Curation Rationale
Usability of Transformer-based models, instability relating to data scarcity, investigation of data augmentation, hyperparameters optimization and cross-lingual transfer on the performance of a question-answering task in French.
### Source Data
#### Initial Data Collection and Normalization
validation: manually collected gold standards, chrf scores and bleu evaluation
#### 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
Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
### Citation Information
```
@inproceedings{cattan:hal-03336060,
  TITLE = {{On the Usability of Transformers-based models for a French Question-Answering task}},
  AUTHOR = {Cattan, Oralie and Servan, Christophe and Rosset, Sophie},
  URL = {https://hal.archives-ouvertes.fr/hal-03336060},
  BOOKTITLE = {{Recent Advances in Natural Language Processing (RANLP)}},
  ADDRESS = {Varna, Bulgaria},
  YEAR = {2021},
  MONTH = Sep,
  PDF = {https://hal.archives-ouvertes.fr/hal-03336060/file/RANLP_2021_transformers_usability.pdf},
  HAL_ID = {hal-03336060},
  HAL_VERSION = {v1},
}
```
task_categories:question-answering task_ids:extractive-qa task_ids:closed-domain-qa annotations_creators:machine-generated language_creators:machine-generated multilinguality:monolingual multilinguality:translation size_categories:10K<n<100K source_datasets:extended|squad language:fr license:cc-by-4.0 region:us
{"annotations_creators": ["machine-generated"], "language_creators": ["machine-generated"], "language": ["fr"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual", "translation"], "size_categories": ["10K<n<100K"], "source_datasets": ["extended|squad"], "task_categories": ["question-answering"], "task_ids": ["extractive-qa", "closed-domain-qa"], "paperswithcode_id": "squad", "pretty_name": "SQuAD-fr"}
TAGS
#task_categories-question-answering #task_ids-extractive-qa #task_ids-closed-domain-qa #annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #multilinguality-translation #size_categories-10K<n<100K #source_datasets-extended|squad #language-French #license-cc-by-4.0 #region-us 

Dataset Card for "squad\_fr"
============================


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


Dataset Description
-------------------


* Paper: On the Usability of Transformers-based models for a French Question-Answering task
* Size of downloaded dataset files: 10 MB
* Size of the generated dataset: 73 MB
* Total amount of disk used: 83 MB


### Dataset Summary


SQuAD-fr:


* a translated version of the Stanford Question Answering Dataset (SQuAD) into French
	+ obtained through automatic translation of the English dataset
* a reading comprehension dataset, consisting of approximately 90K factoid questions on Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage
* serves as a means of data augmentation on FQuAD and PIAF benchmarks


### 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.


Dataset Structure
-----------------


### Data Instances


#### default


* Size of downloaded dataset files: 10 MB
* Size of the generated dataset: 73 MB
* Total amount of disk used: 83 MB
An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### plain\_text


* 'id': a 'string' feature.
* 'title': a 'string' feature.
* 'context': a 'string' feature.
* 'question': a 'string' feature.
* 'answers': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'answer\_start': a 'int32' feature.


### Data Splits



Dataset Creation
----------------


### Curation Rationale


Usability of Transformer-based models, instability relating to data scarcity, investigation of data augmentation, hyperparameters optimization and cross-lingual transfer on the performance of a question-answering task in French.


### Source Data


#### Initial Data Collection and Normalization


validation: manually collected gold standards, chrf scores and bleu evaluation


#### 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


Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)



### Dataset Summary


SQuAD-fr:


* a translated version of the Stanford Question Answering Dataset (SQuAD) into French
	+ obtained through automatic translation of the English dataset
* a reading comprehension dataset, consisting of approximately 90K factoid questions on Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage
* serves as a means of data augmentation on FQuAD and PIAF benchmarks ### 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.


Dataset Structure
----------------- ### Data Instances #### default


* Size of downloaded dataset files: 10 MB
* Size of the generated dataset: 73 MB
* Total amount of disk used: 83 MB
An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### plain\_text


* 'id': a 'string' feature.
* 'title': a 'string' feature.
* 'context': a 'string' feature.
* 'question': a 'string' feature.
* 'answers': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'answer\_start': a 'int32' feature. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale


Usability of Transformer-based models, instability relating to data scarcity, investigation of data augmentation, hyperparameters optimization and cross-lingual transfer on the performance of a question-answering task in French. ### Source Data #### Initial Data Collection and Normalization


validation: manually collected gold standards, chrf scores and bleu evaluation #### 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


Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
TAGS
#task_categories-question-answering #task_ids-extractive-qa #task_ids-closed-domain-qa #annotations_creators-machine-generated #language_creators-machine-generated #multilinguality-monolingual #multilinguality-translation #size_categories-10K<n<100K #source_datasets-extended|squad #language-French #license-cc-by-4.0 #region-us 
 ### Dataset Summary


SQuAD-fr:


* a translated version of the Stanford Question Answering Dataset (SQuAD) into French
	+ obtained through automatic translation of the English dataset
* a reading comprehension dataset, consisting of approximately 90K factoid questions on Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage
* serves as a means of data augmentation on FQuAD and PIAF benchmarks ### 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.


Dataset Structure
----------------- ### Data Instances #### default


* Size of downloaded dataset files: 10 MB
* Size of the generated dataset: 73 MB
* Total amount of disk used: 83 MB
An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### plain\_text


* 'id': a 'string' feature.
* 'title': a 'string' feature.
* 'context': a 'string' feature.
* 'question': a 'string' feature.
* 'answers': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'answer\_start': a 'int32' feature. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale


Usability of Transformer-based models, instability relating to data scarcity, investigation of data augmentation, hyperparameters optimization and cross-lingual transfer on the performance of a question-answering task in French. ### Source Data #### Initial Data Collection and Normalization


validation: manually collected gold standards, chrf scores and bleu evaluation #### 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


Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)