--- annotations_creators: - derived language: - deu - fra - rus - spa license: unknown multilinguality: multilingual source_datasets: - mteb/mlsum task_categories: - text-classification task_ids: - topic-classification dataset_info: - config_name: de features: - name: text dtype: string - name: summary dtype: string - name: topic dtype: string - name: url dtype: string - name: title dtype: string - name: date dtype: string splits: - name: train num_bytes: 846959840 num_examples: 220887 - name: validation num_bytes: 47119541 num_examples: 11394 - name: test num_bytes: 46847612 num_examples: 10701 download_size: 571417481 dataset_size: 940926993 - config_name: es features: - name: text dtype: string - name: summary dtype: string - name: topic dtype: string - name: url dtype: string - name: title dtype: string - name: date dtype: string splits: - name: train num_bytes: 1214558302 num_examples: 266367 - name: validation num_bytes: 50643400 num_examples: 10358 - name: test num_bytes: 71263665 num_examples: 13920 download_size: 825046238 dataset_size: 1336465367 - config_name: fr features: - name: text dtype: string - name: summary dtype: string - name: topic dtype: string - name: url dtype: string - name: title dtype: string - name: date dtype: string splits: - name: train num_bytes: 1471965014 num_examples: 392902 - name: validation num_bytes: 70413212 num_examples: 16059 - name: test num_bytes: 69660288 num_examples: 15828 download_size: 988248158 dataset_size: 1612038514 - config_name: ru features: - name: text dtype: string - name: summary dtype: string - name: topic dtype: string - name: url dtype: string - name: title dtype: string - name: date dtype: string splits: - name: train num_bytes: 257389497 num_examples: 25556 - name: validation num_bytes: 9128497 num_examples: 750 - name: test num_bytes: 9656398 num_examples: 757 download_size: 141914441 dataset_size: 276174392 - config_name: tu features: - name: text dtype: string - name: summary dtype: string - name: topic dtype: string - name: url dtype: string - name: title dtype: string - name: date dtype: string splits: - name: train num_bytes: 641622783 num_examples: 249277 - name: validation num_bytes: 25530661 num_examples: 11565 - name: test num_bytes: 27830212 num_examples: 12775 download_size: 381532936 dataset_size: 694983656 configs: - config_name: de data_files: - split: train path: de/train-* - split: validation path: de/validation-* - split: test path: de/test-* - config_name: es data_files: - split: train path: es/train-* - split: validation path: es/validation-* - split: test path: es/test-* - config_name: fr data_files: - split: train path: fr/train-* - split: validation path: fr/validation-* - split: test path: fr/test-* - config_name: ru data_files: - split: train path: ru/train-* - split: validation path: ru/validation-* - split: test path: ru/test-* - config_name: tu data_files: - split: train path: tu/train-* - split: validation path: tu/validation-* - split: test path: tu/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 | ## 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_tasks(["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 repitory](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{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, Lo{\"\i}c 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("MLSUMClusteringS2S.v2") desc_stats = task.metadata.descriptive_stats ``` ```json { "validation": { "num_samples": 6894, "number_of_characters": 29580726, "min_text_length": 273, "average_text_length": 4290.792863359443, "max_text_length": 56317, "unique_texts": 4307, "min_labels_per_text": 1, "average_labels_per_text": 1.0, "max_labels_per_text": 1129, "unique_labels": 78, "labels": { "7": { "count": 1129 }, "8": { "count": 149 }, "6": { "count": 152 }, "10": { "count": 41 }, "11": { "count": 450 }, "5": { "count": 284 }, "9": { "count": 466 }, "2": { "count": 114 }, "4": { "count": 70 }, "0": { "count": 120 }, "1": { "count": 378 }, "3": { "count": 218 }, "30": { "count": 312 }, "43": { "count": 26 }, "31": { "count": 15 }, "48": { "count": 65 }, "37": { "count": 51 }, "18": { "count": 208 }, "24": { "count": 25 }, "51": { "count": 142 }, "56": { "count": 167 }, "13": { "count": 189 }, "42": { "count": 78 }, "29": { "count": 4 }, "53": { "count": 8 }, "58": { "count": 14 }, "49": { "count": 66 }, "27": { "count": 198 }, "16": { "count": 23 }, "38": { "count": 15 }, "57": { "count": 135 }, "50": { "count": 23 }, "21": { "count": 16 }, "54": { "count": 51 }, "44": { "count": 55 }, "40": { "count": 137 }, "19": { "count": 176 }, "59": { "count": 7 }, "41": { "count": 6 }, "12": { "count": 3 }, "52": { "count": 4 }, "45": { "count": 32 }, "32": { "count": 26 }, "55": { "count": 314 }, "14": { "count": 61 }, "46": { "count": 9 }, "22": { "count": 3 }, "26": { "count": 22 }, "17": { "count": 2 }, "20": { "count": 5 }, "35": { "count": 2 }, "39": { "count": 3 }, "60": { "count": 1 }, "47": { "count": 2 }, "36": { "count": 5 }, "61": { "count": 1 }, "33": { "count": 2 }, "34": { "count": 2 }, "15": { "count": 74 }, "68": { "count": 74 }, "65": { "count": 32 }, "78": { "count": 86 }, "75": { "count": 204 }, "28": { "count": 36 }, "69": { "count": 28 }, "77": { "count": 1 }, "72": { "count": 7 }, "73": { "count": 15 }, "70": { "count": 2 }, "79": { "count": 17 }, "66": { "count": 5 }, "25": { "count": 1 }, "74": { "count": 7 }, "76": { "count": 4 }, "64": { "count": 11 }, "63": { "count": 1 }, "71": { "count": 6 }, "23": { "count": 1 } }, "hf_subset_descriptive_stats": { "de": { "num_samples": 2048, "number_of_characters": 7721299, "min_text_length": 340, "average_text_length": 3770.16552734375, "max_text_length": 17367, "unique_texts": 1764, "min_labels_per_text": 18, "average_labels_per_text": 1.0, "max_labels_per_text": 691, "unique_labels": 12, "labels": { "7": { "count": 691 }, "8": { "count": 37 }, "6": { "count": 130 }, "10": { "count": 37 }, "11": { "count": 448 }, "5": { "count": 98 }, "9": { "count": 457 }, "2": { "count": 46 }, "4": { "count": 27 }, "0": { "count": 39 }, "1": { "count": 20 }, "3": { "count": 18 } } }, "fr": { "num_samples": 2048, "number_of_characters": 7798594, "min_text_length": 340, "average_text_length": 3807.9072265625, "max_text_length": 56261, "unique_texts": 1526, "min_labels_per_text": 1, "average_labels_per_text": 1.0, "max_labels_per_text": 312, "unique_labels": 58, "labels": { "30": { "count": 312 }, "43": { "count": 20 }, "31": { "count": 2 }, "48": { "count": 51 }, "37": { "count": 41 }, "18": { "count": 205 }, "24": { "count": 23 }, "51": { "count": 141 }, "56": { "count": 166 }, "13": { "count": 188 }, "42": { "count": 62 }, "29": { "count": 1 }, "53": { "count": 6 }, "58": { "count": 6 }, "49": { "count": 66 }, "1": { "count": 156 }, "7": { "count": 36 }, "0": { "count": 11 }, "27": { "count": 193 }, "16": { "count": 23 }, "38": { "count": 1 }, "57": { "count": 71 }, "2": { "count": 28 }, "5": { "count": 24 }, "50": { "count": 19 }, "9": { "count": 8 }, "21": { "count": 15 }, "54": { "count": 48 }, "44": { "count": 26 }, "40": { "count": 26 }, "19": { "count": 7 }, "59": { "count": 3 }, "41": { "count": 5 }, "12": { "count": 2 }, "4": { "count": 7 }, "52": { "count": 4 }, "45": { "count": 1 }, "32": { "count": 2 }, "55": { "count": 3 }, "6": { "count": 8 }, "14": { "count": 1 }, "10": { "count": 3 }, "46": { "count": 3 }, "22": { "count": 1 }, "26": { "count": 6 }, "3": { "count": 1 }, "17": { "count": 1 }, "20": { "count": 1 }, "35": { "count": 1 }, "39": { "count": 3 }, "60": { "count": 1 }, "47": { "count": 1 }, "36": { "count": 2 }, "61": { "count": 1 }, "33": { "count": 1 }, "8": { "count": 2 }, "34": { "count": 1 }, "11": { "count": 1 } } }, "ru": { "num_samples": 750, "number_of_characters": 4847491, "min_text_length": 711, "average_text_length": 6463.321333333333, "max_text_length": 32833, "unique_texts": 729, "min_labels_per_text": 13, "average_labels_per_text": 1.0, "max_labels_per_text": 263, "unique_labels": 9, "labels": { "7": { "count": 263 }, "1": { "count": 58 }, "3": { "count": 45 }, "5": { "count": 154 }, "8": { "count": 83 }, "6": { "count": 13 }, "4": { "count": 33 }, "0": { "count": 65 }, "2": { "count": 36 } } }, "es": { "num_samples": 2048, "number_of_characters": 9213342, "min_text_length": 273, "average_text_length": 4498.7021484375, "max_text_length": 56317, "unique_texts": 1746, "min_labels_per_text": 1, "average_labels_per_text": 1.0, "max_labels_per_text": 311, "unique_labels": 71, "labels": { "15": { "count": 74 }, "68": { "count": 74 }, "37": { "count": 10 }, "65": { "count": 32 }, "57": { "count": 64 }, "55": { "count": 311 }, "78": { "count": 86 }, "7": { "count": 139 }, "75": { "count": 204 }, "44": { "count": 29 }, "32": { "count": 24 }, "28": { "count": 36 }, "42": { "count": 16 }, "40": { "count": 111 }, "19": { "count": 169 }, "8": { "count": 27 }, "69": { "count": 28 }, "1": { "count": 144 }, "2": { "count": 4 }, "48": { "count": 14 }, "14": { "count": 60 }, "22": { "count": 2 }, "77": { "count": 1 }, "3": { "count": 154 }, "72": { "count": 7 }, "73": { "count": 15 }, "31": { "count": 13 }, "38": { "count": 14 }, "20": { "count": 4 }, "59": { "count": 4 }, "70": { "count": 2 }, "26": { "count": 16 }, "45": { "count": 31 }, "33": { "count": 1 }, "58": { "count": 8 }, "50": { "count": 4 }, "43": { "count": 6 }, "79": { "count": 17 }, "66": { "count": 5 }, "46": { "count": 6 }, "25": { "count": 1 }, "24": { "count": 2 }, "74": { "count": 7 }, "5": { "count": 8 }, "13": { "count": 1 }, "36": { "count": 3 }, "0": { "count": 5 }, "41": { "count": 1 }, "54": { "count": 3 }, "76": { "count": 4 }, "64": { "count": 11 }, "4": { "count": 3 }, "53": { "count": 2 }, "63": { "count": 1 }, "27": { "count": 5 }, "29": { "count": 3 }, "56": { "count": 1 }, "18": { "count": 3 }, "34": { "count": 1 }, "12": { "count": 1 }, "71": { "count": 6 }, "47": { "count": 1 }, "17": { "count": 1 }, "21": { "count": 1 }, "10": { "count": 1 }, "23": { "count": 1 }, "9": { "count": 1 }, "35": { "count": 1 }, "51": { "count": 1 }, "11": { "count": 1 }, "6": { "count": 1 } } } } }, "test": { "num_samples": 6900, "number_of_characters": 30705479, "min_text_length": 288, "average_text_length": 4450.069420289855, "max_text_length": 135921, "unique_texts": 4336, "min_labels_per_text": 1, "average_labels_per_text": 1.0, "max_labels_per_text": 1040, "unique_labels": 80, "labels": { "5": { "count": 285 }, "11": { "count": 453 }, "9": { "count": 469 }, "7": { "count": 1040 }, "4": { "count": 65 }, "8": { "count": 160 }, "2": { "count": 132 }, "3": { "count": 218 }, "6": { "count": 137 }, "1": { "count": 349 }, "10": { "count": 64 }, "0": { "count": 154 }, "33": { "count": 160 }, "24": { "count": 179 }, "19": { "count": 350 }, "35": { "count": 367 }, "59": { "count": 53 }, "69": { "count": 15 }, "15": { "count": 61 }, "60": { "count": 18 }, "56": { "count": 2 }, "65": { "count": 183 }, "40": { "count": 7 }, "58": { "count": 112 }, "55": { "count": 86 }, "47": { "count": 66 }, "23": { "count": 27 }, "25": { "count": 6 }, "66": { "count": 109 }, "18": { "count": 22 }, "41": { "count": 61 }, "63": { "count": 41 }, "29": { "count": 66 }, "30": { "count": 24 }, "32": { "count": 8 }, "54": { "count": 56 }, "49": { "count": 82 }, "44": { "count": 140 }, "46": { "count": 38 }, "57": { "count": 239 }, "48": { "count": 49 }, "17": { "count": 4 }, "13": { "count": 3 }, "61": { "count": 8 }, "68": { "count": 22 }, "37": { "count": 3 }, "50": { "count": 10 }, "26": { "count": 13 }, "43": { "count": 4 }, "16": { "count": 98 }, "64": { "count": 21 }, "51": { "count": 2 }, "38": { "count": 2 }, "67": { "count": 100 }, "70": { "count": 11 }, "42": { "count": 6 }, "14": { "count": 3 }, "31": { "count": 33 }, "12": { "count": 1 }, "36": { "count": 2 }, "27": { "count": 3 }, "53": { "count": 8 }, "74": { "count": 181 }, "22": { "count": 2 }, "76": { "count": 102 }, "72": { "count": 12 }, "71": { "count": 8 }, "52": { "count": 17 }, "28": { "count": 4 }, "79": { "count": 23 }, "34": { "count": 25 }, "62": { "count": 2 }, "20": { "count": 2 }, "75": { "count": 2 }, "73": { "count": 4 }, "21": { "count": 1 }, "39": { "count": 1 }, "45": { "count": 1 }, "77": { "count": 1 }, "78": { "count": 2 } }, "hf_subset_descriptive_stats": { "de": { "num_samples": 2048, "number_of_characters": 8183989, "min_text_length": 660, "average_text_length": 3996.08837890625, "max_text_length": 25967, "unique_texts": 1715, "min_labels_per_text": 20, "average_labels_per_text": 1.0, "max_labels_per_text": 692, "unique_labels": 12, "labels": { "5": { "count": 106 }, "11": { "count": 450 }, "9": { "count": 467 }, "7": { "count": 692 }, "4": { "count": 24 }, "8": { "count": 42 }, "2": { "count": 45 }, "3": { "count": 20 }, "6": { "count": 103 }, "1": { "count": 24 }, "10": { "count": 40 }, "0": { "count": 35 } } }, "fr": { "num_samples": 2048, "number_of_characters": 7735699, "min_text_length": 291, "average_text_length": 3777.19677734375, "max_text_length": 50088, "unique_texts": 1524, "min_labels_per_text": 1, "average_labels_per_text": 1.0, "max_labels_per_text": 333, "unique_labels": 61, "labels": { "33": { "count": 160 }, "24": { "count": 178 }, "19": { "count": 179 }, "7": { "count": 5 }, "35": { "count": 333 }, "59": { "count": 1 }, "69": { "count": 8 }, "1": { "count": 158 }, "15": { "count": 1 }, "60": { "count": 7 }, "56": { "count": 1 }, "2": { "count": 28 }, "65": { "count": 154 }, "40": { "count": 1 }, "58": { "count": 111 }, "55": { "count": 85 }, "47": { "count": 58 }, "23": { "count": 24 }, "10": { "count": 23 }, "25": { "count": 5 }, "66": { "count": 107 }, "18": { "count": 17 }, "41": { "count": 36 }, "63": { "count": 41 }, "29": { "count": 46 }, "30": { "count": 20 }, "32": { "count": 5 }, "54": { "count": 54 }, "49": { "count": 37 }, "44": { "count": 28 }, "46": { "count": 5 }, "6": { "count": 19 }, "57": { "count": 11 }, "48": { "count": 21 }, "0": { "count": 10 }, "9": { "count": 1 }, "17": { "count": 4 }, "13": { "count": 1 }, "61": { "count": 4 }, "68": { "count": 2 }, "37": { "count": 3 }, "50": { "count": 4 }, "26": { "count": 13 }, "43": { "count": 3 }, "11": { "count": 2 }, "8": { "count": 6 }, "5": { "count": 7 }, "16": { "count": 2 }, "64": { "count": 3 }, "51": { "count": 2 }, "38": { "count": 1 }, "67": { "count": 1 }, "70": { "count": 2 }, "42": { "count": 1 }, "14": { "count": 3 }, "31": { "count": 1 }, "4": { "count": 1 }, "12": { "count": 1 }, "36": { "count": 1 }, "27": { "count": 1 }, "53": { "count": 1 } } }, "ru": { "num_samples": 756, "number_of_characters": 5128031, "min_text_length": 395, "average_text_length": 6783.109788359789, "max_text_length": 135921, "unique_texts": 732, "min_labels_per_text": 15, "average_labels_per_text": 1.0, "max_labels_per_text": 203, "unique_labels": 9, "labels": { "6": { "count": 15 }, "5": { "count": 161 }, "4": { "count": 38 }, "0": { "count": 108 }, "7": { "count": 203 }, "2": { "count": 51 }, "1": { "count": 43 }, "8": { "count": 82 }, "3": { "count": 55 } } }, "es": { "num_samples": 2048, "number_of_characters": 9657760, "min_text_length": 288, "average_text_length": 4715.703125, "max_text_length": 85710, "unique_texts": 1785, "min_labels_per_text": 1, "average_labels_per_text": 1.0, "max_labels_per_text": 228, "unique_labels": 71, "labels": { "41": { "count": 25 }, "2": { "count": 8 }, "74": { "count": 181 }, "64": { "count": 18 }, "22": { "count": 2 }, "16": { "count": 96 }, "67": { "count": 99 }, "1": { "count": 124 }, "3": { "count": 143 }, "65": { "count": 29 }, "48": { "count": 28 }, "57": { "count": 228 }, "15": { "count": 60 }, "49": { "count": 45 }, "29": { "count": 20 }, "19": { "count": 171 }, "59": { "count": 52 }, "7": { "count": 140 }, "44": { "count": 112 }, "31": { "count": 32 }, "47": { "count": 8 }, "76": { "count": 102 }, "8": { "count": 30 }, "72": { "count": 12 }, "71": { "count": 8 }, "52": { "count": 17 }, "5": { "count": 11 }, "46": { "count": 33 }, "28": { "count": 4 }, "79": { "count": 23 }, "69": { "count": 7 }, "35": { "count": 34 }, "30": { "count": 4 }, "43": { "count": 1 }, "61": { "count": 4 }, "42": { "count": 5 }, "60": { "count": 11 }, "34": { "count": 25 }, "18": { "count": 5 }, "68": { "count": 20 }, "40": { "count": 6 }, "24": { "count": 1 }, "56": { "count": 1 }, "27": { "count": 2 }, "70": { "count": 9 }, "62": { "count": 2 }, "58": { "count": 1 }, "13": { "count": 2 }, "32": { "count": 3 }, "4": { "count": 2 }, "53": { "count": 7 }, "20": { "count": 2 }, "36": { "count": 1 }, "23": { "count": 3 }, "75": { "count": 2 }, "50": { "count": 6 }, "0": { "count": 1 }, "73": { "count": 4 }, "66": { "count": 2 }, "54": { "count": 2 }, "21": { "count": 1 }, "9": { "count": 1 }, "38": { "count": 1 }, "55": { "count": 1 }, "10": { "count": 1 }, "39": { "count": 1 }, "45": { "count": 1 }, "77": { "count": 1 }, "11": { "count": 1 }, "78": { "count": 2 }, "25": { "count": 1 } } } } } } ```
--- *This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*