Datasets:

mteb
/

MLSUMClusteringS2S.v2

annotations_creators:
  - derived
language:
  - deu
  - fra
  - rus
  - spa
license: unknown
multilinguality: multilingual
source_datasets:
  - mteb/mlsum
  - mteb/mlsum
task_categories:
  - text-classification
task_ids:
  - topic-classification
dataset_info:
  - config_name: de
    features:
      - name: sentences
        dtype: string
      - name: labels
        dtype: int64
    splits:
      - name: validation
        num_bytes: 7851569
        num_examples: 2048
      - name: test
        num_bytes: 8321519
        num_examples: 2048
    download_size: 10289335
    dataset_size: 16173088
  - config_name: es
    features:
      - name: sentences
        dtype: string
      - name: labels
        dtype: int64
    splits:
      - name: validation
        num_bytes: 9449236
        num_examples: 2048
      - name: test
        num_bytes: 9905324
        num_examples: 2048
    download_size: 12116305
    dataset_size: 19354560
  - config_name: fr
    features:
      - name: sentences
        dtype: string
      - name: labels
        dtype: int64
    splits:
      - name: validation
        num_bytes: 8233842
        num_examples: 2048
      - name: test
        num_bytes: 8169369
        num_examples: 2048
    download_size: 10111210
    dataset_size: 16403211
  - config_name: ru
    features:
      - name: sentences
        dtype: string
      - name: labels
        dtype: int64
    splits:
      - name: validation
        num_bytes: 8827403
        num_examples: 750
      - name: test
        num_bytes: 9342909
        num_examples: 756
    download_size: 9299062
    dataset_size: 18170312
configs:
  - config_name: de
    data_files:
      - split: validation
        path: de/validation-*
      - split: test
        path: de/test-*
  - config_name: es
    data_files:
      - split: validation
        path: es/validation-*
      - split: test
        path: es/test-*
  - config_name: fr
    data_files:
      - split: validation
        path: fr/validation-*
      - split: test
        path: fr/test-*
  - config_name: ru
    data_files:
      - split: validation
        path: ru/validation-*
      - split: test
        path: ru/test-*
tags:
  - mteb
  - text

MLSUMClusteringS2S.v2

An MTEB dataset

Massive Text Embedding Benchmark

Clustering of newspaper article contents and titles from MLSUM dataset. Clustering of 10 sets on the newpaper article topics.


Task category	t2c
Domains	News, Written
Reference	https://huggingface.co/datasets/mteb/mlsum

Source datasets:

How to evaluate on this task

You can evaluate an embedding model on this dataset using the following code:

import mteb

task = mteb.get_task("MLSUMClusteringS2S.v2")
evaluator = mteb.MTEB([task])

model = mteb.get_model(YOUR_MODEL)
evaluator.run(model)

To learn more about how to run models on mteb task check out the GitHub repository.

Citation

If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing as a part of the MMTEB Contribution.


@article{scialom2020mlsum,
  author = {Scialom, Thomas and Dray, Paul-Alexis and Lamprier, Sylvain and Piwowarski, Benjamin and Staiano, Jacopo},
  journal = {arXiv preprint arXiv:2004.14900},
  title = {MLSUM: The Multilingual Summarization Corpus},
  year = {2020},
}


@article{enevoldsen2025mmtebmassivemultilingualtext,
  title={MMTEB: Massive Multilingual Text Embedding Benchmark},
  author={Kenneth Enevoldsen and Isaac Chung and Imene Kerboua and Márton Kardos and Ashwin Mathur and David Stap and Jay Gala and Wissam Siblini and Dominik Krzemiński and Genta Indra Winata and Saba Sturua and Saiteja Utpala and Mathieu Ciancone and Marion Schaeffer and Gabriel Sequeira and Diganta Misra and Shreeya Dhakal and Jonathan Rystrøm and Roman Solomatin and Ömer Çağatan and Akash Kundu and Martin Bernstorff and Shitao Xiao and Akshita Sukhlecha and Bhavish Pahwa and Rafał Poświata and Kranthi Kiran GV and Shawon Ashraf and Daniel Auras and Björn Plüster and Jan Philipp Harries and Loïc Magne and Isabelle Mohr and Mariya Hendriksen and Dawei Zhu and Hippolyte Gisserot-Boukhlef and Tom Aarsen and Jan Kostkan and Konrad Wojtasik and Taemin Lee and Marek Šuppa and Crystina Zhang and Roberta Rocca and Mohammed Hamdy and Andrianos Michail and John Yang and Manuel Faysse and Aleksei Vatolin and Nandan Thakur and Manan Dey and Dipam Vasani and Pranjal Chitale and Simone Tedeschi and Nguyen Tai and Artem Snegirev and Michael Günther and Mengzhou Xia and Weijia Shi and Xing Han Lù and Jordan Clive and Gayatri Krishnakumar and Anna Maksimova and Silvan Wehrli and Maria Tikhonova and Henil Panchal and Aleksandr Abramov and Malte Ostendorff and Zheng Liu and Simon Clematide and Lester James Miranda and Alena Fenogenova and Guangyu Song and Ruqiya Bin Safi and Wen-Ding Li and Alessia Borghini and Federico Cassano and Hongjin Su and Jimmy Lin and Howard Yen and Lasse Hansen and Sara Hooker and Chenghao Xiao and Vaibhav Adlakha and Orion Weller and Siva Reddy and Niklas Muennighoff},
  publisher = {arXiv},
  journal={arXiv preprint arXiv:2502.13595},
  year={2025},
  url={https://arxiv.org/abs/2502.13595},
  doi = {10.48550/arXiv.2502.13595},
}

@article{muennighoff2022mteb,
  author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Loïc and Reimers, Nils},
  title = {MTEB: Massive Text Embedding Benchmark},
  publisher = {arXiv},
  journal={arXiv preprint arXiv:2210.07316},
  year = {2022}
  url = {https://arxiv.org/abs/2210.07316},
  doi = {10.48550/ARXIV.2210.07316},
}

Dataset Statistics

The following code contains the descriptive statistics from the task. These can also be obtained using:

import mteb

task = mteb.get_task("MLSUMClusteringS2S.v2")

desc_stats = task.metadata.descriptive_stats

{}

This dataset card was automatically generated using MTEB