CATIE-AQ/frenchSUM

Dataset information

Dataset concatenating Summarization datasets available in French and open-source.
There are a total of 841,673 rows, of which 788,358 are for training, 26,935 for validation and 26,380 for testing.

Usage

from datasets import load_dataset
dataset = load_dataset("CATIE-AQ/frenchSUM")

Dataset

Details of rows

Dataset Original	Splits	Note
GEM/xwikis	323,726 train / 7,339 validation / 6,992 test	We only keep the French split
maurya/alpaca_motivations_sommaires	7,801 train
csebuetnlp/CrossSum	8,648 train / 1,083 validation / 1,083 test	We only keep the French split Perhaps not a great dataset (there's information in the summary that isn't in the original text)
csebuetnlp/xlsum	8,697 train / 1,086 validation / 1,086 test	We only keep the French split
orange_sum	21,401 train / 1,500 validation / 1,500 test	We use the abstract split
mlsum	392,017 train / 16,059 validation / 15,820 test	We only keep the French split
fr_covid_news_8k	8,084 train
FakeNewsDetectionFr	1,260 train
MassiveSumm_short	2,500 train	We only keep the French split
MassiveSumm_long	684 train	We only keep the French split
wikinews	22,463 train	We only keep the French split

Removing duplicate data and leaks

The sum of the values of the datasets listed here gives the following result:

DatasetDict({
    train: Dataset({
        features: ['text', 'summary', 'dataset'],
        num_rows: 797281
    })
    validation: Dataset({
        features: ['text', 'summary', 'dataset'],
        num_rows: 27067
    })
    test: Dataset({
        features: ['text', 'summary', 'dataset'],
        num_rows: 26481
    })
})

However, a data item in training split A may not be in A's test split, but may be present in B's test set, creating a leak when we create the A+B dataset.
The same logic applies to duplicate data. So we need to make sure we remove them.
After our clean-up, we finally have the following numbers:

DatasetDict({
    train: Dataset({
        features: ['text', 'summary', 'dataset'],
        num_rows: 788358
    })
    validation: Dataset({
        features: ['text', 'summary', 'dataset'],
        num_rows: 26935
    })
    test: Dataset({
        features: ['text', 'summary', 'dataset'],
        num_rows: 26380
    })
})

Note that an additional cleanup has been applied to all rows, removing all URLs and emojis present in the articles.

Columns

dataset_train = dataset['train'].to_pandas()
dataset_train.head()

    text                                                   summary                                             dataset
0 	L'astronomie est considérée comme la plus anci... 	L’astronomie est la science de l’observation d...   xwikis
1 	L'origine du mot est anglaise, "tourist", qui ... 	Le mot tourisme désigne le fait de voyager pou...   xwikis
2 	Étymologiquement, le mot français "philosophie... 	La philosophie, du grec ancien "φιλοσοφία" (com...   xwikis
3 	Le terme biologie est formé par la composition... 	La biologie (du grec "bios" « la vie » et "log...   xwikis
4 	Trois étymologies sont fréquemment citées, mai... 	La chimie est une science de la nature qui étu...   xwikis

• the text column contains the text
• the summary column contains text summary
• the dataset column identifies the row's original dataset (if you wish to apply filters to it)

Split

• train corresponds to the concatenation of xwikis + alpaca_motivations_sommaires + cross_sum + xlsum + orange_sum + mlsum + fr_covid_news_8k + FakeNewsDetectionFr + MassiveSumm_short+ MassiveSumm_long + wikinews
• validation corresponds to the concatenation of xwikis + cross_sum + xlsum + orange_sum + mlsum
• test corresponds to the concatenation of xwikis + cross_sum + xlsum + orange_sum + mlsum

Citations

alpaca_motivations_sommaires

Dataset by Amaury FOURET (2023) 
Hugging Face repository: https://huggingface.co/datasets/maurya/alpaca_motivations_sommaires

FakeNewsDetectionFr

Dataset by Gregory LANG (2019) 
Hugging Face repository: https://github.com/jeugregg/FakeNewsDetectionFr

fr_covid_news_8k

@dataset{covidfrenchnews,  
  author = {Gustave Cortal},  
  year = {2021},  
  month = {03},  
  title = {COVID-19: French news dataset},  
  url = {https://www.gustavecortal.com}}

CrossSum

@misc{bhattacharjee2023crosssum,  
      title={CrossSum: Beyond English-Centric Cross-Lingual Summarization for 1,500+ Language Pairs},  
      author={Abhik Bhattacharjee and Tahmid Hasan and Wasi Uddin Ahmad and Yuan-Fang Li and Yong-Bin Kang and Rifat Shahriyar},  
      year={2023},  
      eprint={2112.08804},  
      archivePrefix={arXiv},  
      primaryClass={cs.CL}}

mlsum

@inproceedings{scialom-etal-2020-mlsum,  
    title = "{MLSUM}: The Multilingual Summarization Corpus",   
    author = "Scialom, Thomas and Dray, Paul-Alexis  and Lamprier, Sylvain and Piwowarski, Benjamin and Staiano, Jacopo",
    editor = "Webber, Bonnie and Cohn, Trevor and He, Yulan and Liu, Yang",  
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",  
    month = nov,  
    year = "2020",  
    address = "Online",  
    publisher = "Association for Computational Linguistics",  
    url = "https://aclanthology.org/2020.emnlp-main.647",  
    doi = "10.18653/v1/2020.emnlp-main.647",  
    pages = "8051--8067"}

orange_sum

@article{eddine2020barthez,  
  title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model},  
  author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis},  
  journal={arXiv preprint arXiv:2010.12321},  
  year={2020}}

xlsum

@inproceedings{hasan-etal-2021-xl,  
    title = "{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages",  
    author = "Hasan, Tahmid and Bhattacharjee, Abhik and Islam, Md. Saiful  and Mubasshir, Kazi and Li, Yuan-Fang and Kang, Yong-Bin and Rahman, M. Sohel and Shahriyar, Rifat",  
    editor = "Zong, Chengqing  and Xia, Fei and Li, Wenjie and Navigli, Roberto",  
    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",  
    month = aug,  
    year = "2021",  
    address = "Online",  
    publisher = "Association for Computational Linguistics",  
    url = "https://aclanthology.org/2021.findings-acl.413",  
    doi = "10.18653/v1/2021.findings-acl.413",  
    pages = "4693--4703"}

xwikis

@misc{perezbeltrachini2022models,  
      title={Models and Datasets for Cross-Lingual Summarisation},  
      author={Laura Perez-Beltrachini and Mirella Lapata},  
      year={2022},  
      eprint={2202.09583},  
      archivePrefix={arXiv},  
      primaryClass={cs.CL}}

MassiveSumm

@inproceedings{djamshidi-etal-2021-massivesumm,
title = "MassiveSumm: A Very Large-Scale, Very Multilingual News Summarisation Dataset",
author = "Djamshidi, Amir Abbas and Mehrabi, Pegah and Paun, Andrei and Sagot, Beno{^i}t",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.emnlp-main.303",
pages = "3749--3765",
}

wikinews

Dataset by Malte OSTENDORFF (2024) 
Hugging Face repository: https://huggingface.co/datasets/malteos/wikinews

FrenchSUM

@misc {frenchSUM,   
    author       = { {BOURDOIS, Loïck} },  
    organization  = { {Centre Aquitain des Technologies de l'Information et Electroniques} },  
    title        = { frenchSUM (Revision 299b07c) },  
    year         = 2023,  
    url          = { https://huggingface.co/datasets/CATIE-AQ/frenchSUM },  
    doi          = { 10.57967/hf/6447 },  
    publisher    = { Hugging Face } }

License

cc-by-4.0