--- annotations_creators: - derived language: - bos - cat - ces - dan - eus - glv - ilo - kur - lav - min - mlt - sco - sqi - wln license: cc-by-sa-3.0 multilinguality: multilingual source_datasets: - ryzzlestrizzle/multi-wiki-clustering-p2p - ryzzlestrizzle/multi-wiki-clustering-p2p task_categories: - text-classification task_ids: [] dataset_info: - config_name: bs features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 2188488 num_examples: 2048 download_size: 1123149 dataset_size: 2188488 - config_name: ca features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 1282506 num_examples: 2048 download_size: 788051 dataset_size: 1282506 - config_name: cs features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 1472753 num_examples: 2048 download_size: 881131 dataset_size: 1472753 - config_name: da features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 1618633 num_examples: 2048 download_size: 878161 dataset_size: 1618633 - config_name: eu features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 855822 num_examples: 2048 download_size: 360856 dataset_size: 855822 - config_name: gv features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 783569 num_examples: 2048 download_size: 283454 dataset_size: 783569 - config_name: ilo features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 1294019 num_examples: 2048 download_size: 447260 dataset_size: 1294019 - config_name: ku features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 946868 num_examples: 2048 download_size: 442262 dataset_size: 946868 - config_name: lv features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 1668332 num_examples: 2048 download_size: 879950 dataset_size: 1668332 - config_name: min features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 1320670 num_examples: 2048 download_size: 377039 dataset_size: 1320670 - config_name: mt features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 1756275 num_examples: 2048 download_size: 636171 dataset_size: 1756275 - config_name: sco features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 2219329 num_examples: 2048 download_size: 1136066 dataset_size: 2219329 - config_name: sq features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 931594 num_examples: 2048 download_size: 517905 dataset_size: 931594 - config_name: wa features: - name: sentences dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 479096 num_examples: 2048 download_size: 206105 dataset_size: 479096 configs: - config_name: bs data_files: - split: test path: bs/test-* - config_name: ca data_files: - split: test path: ca/test-* - config_name: cs data_files: - split: test path: cs/test-* - config_name: da data_files: - split: test path: da/test-* - config_name: eu data_files: - split: test path: eu/test-* - config_name: gv data_files: - split: test path: gv/test-* - config_name: ilo data_files: - split: test path: ilo/test-* - config_name: ku data_files: - split: test path: ku/test-* - config_name: lv data_files: - split: test path: lv/test-* - config_name: min data_files: - split: test path: min/test-* - config_name: mt data_files: - split: test path: mt/test-* - config_name: sco data_files: - split: test path: sco/test-* - config_name: sq data_files: - split: test path: sq/test-* - config_name: wa data_files: - split: test path: wa/test-* tags: - mteb - text ---

WikiClusteringP2P.v2

An MTEB dataset
Massive Text Embedding Benchmark
Clustering of wikipedia articles inspired by BlubrbsClusteringP2P. Labels are taken from top-level categories of the respective languages (e.g., https://lv.wikipedia.org/wiki/Kategorija:Pamatkategorijas). | | | |---------------|---------------------------------------------| | Task category | t2c | | Domains | Encyclopaedic, Written | | Reference | https://github.com/Rysias/wiki-clustering | Source datasets: - [ryzzlestrizzle/multi-wiki-clustering-p2p](https://huggingface.co/datasets/ryzzlestrizzle/multi-wiki-clustering-p2p) - [ryzzlestrizzle/multi-wiki-clustering-p2p](https://huggingface.co/datasets/ryzzlestrizzle/multi-wiki-clustering-p2p) ## How to evaluate on this task You can evaluate an embedding model on this dataset using the following code: ```python import mteb task = mteb.get_task("WikiClusteringP2P.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](https://github.com/embeddings-benchmark/mteb). ## Citation If you use this dataset, please cite the dataset as well as [mteb](https://github.com/embeddings-benchmark/mteb), as this dataset likely includes additional processing as a part of the [MMTEB Contribution](https://github.com/embeddings-benchmark/mteb/tree/main/docs/mmteb). ```bibtex @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
Dataset Statistics The following code contains the descriptive statistics from the task. These can also be obtained using: ```python import mteb task = mteb.get_task("WikiClusteringP2P.v2") desc_stats = task.metadata.descriptive_stats ``` ```json { "test": { "num_samples": 28672, "text_statistics": { "total_text_length": 18055981, "min_text_length": 1, "average_text_length": 629.7426409040179, "max_text_length": 69506, "unique_texts": 23102 }, "image_statistics": null, "labels_statistics": { "min_labels_per_text": 1, "average_label_per_text": 1.0, "max_labels_per_text": 1, "unique_labels": 39, "labels": { "16": { "count": 541 }, "3": { "count": 1607 }, "12": { "count": 846 }, "0": { "count": 2410 }, "15": { "count": 878 }, "11": { "count": 864 }, "6": { "count": 787 }, "9": { "count": 654 }, "14": { "count": 966 }, "8": { "count": 1389 }, "2": { "count": 2428 }, "10": { "count": 839 }, "1": { "count": 1370 }, "4": { "count": 2942 }, "7": { "count": 2514 }, "5": { "count": 1490 }, "13": { "count": 918 }, "19": { "count": 315 }, "17": { "count": 711 }, "20": { "count": 345 }, "18": { "count": 800 }, "24": { "count": 467 }, "25": { "count": 928 }, "21": { "count": 62 }, "26": { "count": 270 }, "22": { "count": 186 }, "23": { "count": 36 }, "27": { "count": 465 }, "28": { "count": 62 }, "36": { "count": 139 }, "32": { "count": 57 }, "38": { "count": 43 }, "30": { "count": 52 }, "34": { "count": 80 }, "33": { "count": 75 }, "35": { "count": 62 }, "31": { "count": 63 }, "37": { "count": 8 }, "29": { "count": 3 } } } } } ```
--- *This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*