--- annotations_creators: - human-annotated language: - bbc - bew - bug - jav - mad - mak - min - mui - rej - sun license: apache-2.0 multilinguality: multilingual task_categories: - text-classification task_ids: - topic-classification dataset_info: - config_name: bew features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 2220747 num_examples: 2650 - name: validation num_bytes: 362685 num_examples: 435 - name: test num_bytes: 672817 num_examples: 800 download_size: 2004559 dataset_size: 3256249 - config_name: btk features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 944040 num_examples: 1350 - name: validation num_bytes: 195369 num_examples: 275 - name: test num_bytes: 347847 num_examples: 500 download_size: 900271 dataset_size: 1487256 - config_name: bug features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 70660 num_examples: 93 - name: validation num_bytes: 38034 num_examples: 50 - name: test num_bytes: 229420 num_examples: 300 download_size: 211189 dataset_size: 338114 - config_name: jav features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 1874481 num_examples: 2650 - name: validation num_bytes: 316470 num_examples: 448 - name: test num_bytes: 570020 num_examples: 800 download_size: 1656133 dataset_size: 2760971 - config_name: mad features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 1317275 num_examples: 1800 - name: validation num_bytes: 267502 num_examples: 367 - name: test num_bytes: 513718 num_examples: 700 download_size: 1305204 dataset_size: 2098495 - config_name: mak features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 1108367 num_examples: 1500 - name: validation num_bytes: 277160 num_examples: 376 - name: test num_bytes: 517192 num_examples: 700 download_size: 1145982 dataset_size: 1902719 - config_name: min features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 1795445 num_examples: 2400 - name: validation num_bytes: 301552 num_examples: 399 - name: test num_bytes: 599119 num_examples: 800 download_size: 1582344 dataset_size: 2696116 - config_name: mui features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 135609 num_examples: 168 - name: validation num_bytes: 65749 num_examples: 80 - name: test num_bytes: 324566 num_examples: 400 download_size: 318343 dataset_size: 525924 - config_name: rej features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 79235 num_examples: 105 - name: validation num_bytes: 38275 num_examples: 50 - name: test num_bytes: 266553 num_examples: 350 download_size: 219840 dataset_size: 384063 - config_name: sun features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 2191367 num_examples: 2800 - name: validation num_bytes: 369686 num_examples: 468 - name: test num_bytes: 701832 num_examples: 900 download_size: 1965937 dataset_size: 3262885 configs: - config_name: bew data_files: - split: train path: bew/train-* - split: validation path: bew/validation-* - split: test path: bew/test-* - config_name: btk data_files: - split: train path: btk/train-* - split: validation path: btk/validation-* - split: test path: btk/test-* - config_name: bug data_files: - split: train path: bug/train-* - split: validation path: bug/validation-* - split: test path: bug/test-* - config_name: jav data_files: - split: train path: jav/train-* - split: validation path: jav/validation-* - split: test path: jav/test-* - config_name: mad data_files: - split: train path: mad/train-* - split: validation path: mad/validation-* - split: test path: mad/test-* - config_name: mak data_files: - split: train path: mak/train-* - split: validation path: mak/validation-* - split: test path: mak/test-* - config_name: min data_files: - split: train path: min/train-* - split: validation path: min/validation-* - split: test path: min/test-* - config_name: mui data_files: - split: train path: mui/train-* - split: validation path: mui/validation-* - split: test path: mui/test-* - config_name: rej data_files: - split: train path: rej/train-* - split: validation path: rej/validation-* - split: test path: rej/test-* - config_name: sun data_files: - split: train path: sun/train-* - split: validation path: sun/validation-* - split: test path: sun/test-* tags: - mteb - text ---

NusaParagraphTopicClassification

An MTEB dataset
Massive Text Embedding Benchmark
NusaParagraphTopicClassification is a multi-class topic classification on 10 Indonesian languages. | | | |---------------|---------------------------------------------| | Task category | t2c | | Domains | Non-fiction, Fiction, Written | | Reference | https://github.com/IndoNLP/nusa-writes | ## 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(["NusaParagraphTopicClassification"]) 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 @inproceedings{cahyawijaya-etal-2023-nusawrites, address = {Nusa Dua, Bali}, author = {Cahyawijaya, Samuel and Lovenia, Holy and Koto, Fajri and Adhista, Dea and Dave, Emmanuel and Oktavianti, Sarah and Akbar, Salsabil and Lee, Jhonson and Shadieq, Nuur and Cenggoro, Tjeng Wawan and Linuwih, Hanung and Wilie, Bryan and Muridan, Galih and Winata, Genta and Moeljadi, David and Aji, Alham Fikri and Purwarianti, Ayu and Fung, Pascale}, booktitle = {Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)}, editor = {Park, Jong C. and Arase, Yuki and Hu, Baotian and Lu, Wei and Wijaya, Derry and Purwarianti, Ayu and Krisnadhi, Adila Alfa}, month = nov, pages = {921--945}, publisher = {Association for Computational Linguistics}, title = {NusaWrites: Constructing High-Quality Corpora for Underrepresented and Extremely Low-Resource Languages}, url = {https://aclanthology.org/2023.ijcnlp-main.60}, year = {2023}, } @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("NusaParagraphTopicClassification") desc_stats = task.metadata.descriptive_stats ``` ```json { "test": { "num_samples": 6250, "number_of_characters": 4629468, "number_texts_intersect_with_train": 1, "min_text_length": 502, "average_text_length": 740.71488, "max_text_length": 1849, "unique_text": 6250, "unique_labels": 8, "labels": { "0": { "count": 1198 }, "3": { "count": 778 }, "1": { "count": 851 }, "7": { "count": 440 }, "5": { "count": 580 }, "2": { "count": 928 }, "6": { "count": 819 }, "4": { "count": 656 } }, "hf_subset_descriptive_stats": { "btk": { "num_samples": 500, "number_of_characters": 341829, "number_texts_intersect_with_train": 0, "min_text_length": 530, "average_text_length": 683.658, "max_text_length": 1777, "unique_text": 500, "unique_labels": 8, "labels": { "0": { "count": 110 }, "3": { "count": 64 }, "1": { "count": 49 }, "7": { "count": 31 }, "5": { "count": 53 }, "2": { "count": 84 }, "6": { "count": 48 }, "4": { "count": 61 } } }, "bew": { "num_samples": 800, "number_of_characters": 648577, "number_texts_intersect_with_train": 0, "min_text_length": 561, "average_text_length": 810.72125, "max_text_length": 1849, "unique_text": 800, "unique_labels": 8, "labels": { "6": { "count": 119 }, "4": { "count": 71 }, "0": { "count": 143 }, "7": { "count": 71 }, "1": { "count": 122 }, "3": { "count": 100 }, "5": { "count": 74 }, "2": { "count": 100 } } }, "bug": { "num_samples": 300, "number_of_characters": 225792, "number_texts_intersect_with_train": 0, "min_text_length": 594, "average_text_length": 752.64, "max_text_length": 1159, "unique_text": 300, "unique_labels": 8, "labels": { "7": { "count": 33 }, "4": { "count": 13 }, "1": { "count": 33 }, "5": { "count": 37 }, "0": { "count": 65 }, "3": { "count": 71 }, "2": { "count": 33 }, "6": { "count": 15 } } }, "jav": { "num_samples": 800, "number_of_characters": 560251, "number_texts_intersect_with_train": 0, "min_text_length": 578, "average_text_length": 700.31375, "max_text_length": 1190, "unique_text": 800, "unique_labels": 8, "labels": { "4": { "count": 101 }, "6": { "count": 125 }, "1": { "count": 112 }, "3": { "count": 94 }, "7": { "count": 36 }, "2": { "count": 106 }, "5": { "count": 113 }, "0": { "count": 113 } } }, "mad": { "num_samples": 700, "number_of_characters": 504078, "number_texts_intersect_with_train": 0, "min_text_length": 583, "average_text_length": 720.1114285714285, "max_text_length": 1128, "unique_text": 700, "unique_labels": 8, "labels": { "1": { "count": 107 }, "7": { "count": 53 }, "6": { "count": 94 }, "0": { "count": 187 }, "3": { "count": 61 }, "5": { "count": 16 }, "4": { "count": 59 }, "2": { "count": 123 } } }, "mak": { "num_samples": 700, "number_of_characters": 506143, "number_texts_intersect_with_train": 0, "min_text_length": 526, "average_text_length": 723.0614285714286, "max_text_length": 1153, "unique_text": 700, "unique_labels": 8, "labels": { "0": { "count": 166 }, "4": { "count": 69 }, "6": { "count": 82 }, "1": { "count": 96 }, "7": { "count": 53 }, "2": { "count": 108 }, "3": { "count": 94 }, "5": { "count": 32 } } }, "min": { "num_samples": 800, "number_of_characters": 589491, "number_texts_intersect_with_train": 1, "min_text_length": 541, "average_text_length": 736.86375, "max_text_length": 1571, "unique_text": 800, "unique_labels": 8, "labels": { "6": { "count": 93 }, "3": { "count": 78 }, "0": { "count": 156 }, "4": { "count": 73 }, "5": { "count": 101 }, "7": { "count": 59 }, "2": { "count": 128 }, "1": { "count": 112 } } }, "mui": { "num_samples": 400, "number_of_characters": 319747, "number_texts_intersect_with_train": 0, "min_text_length": 593, "average_text_length": 799.3675, "max_text_length": 1524, "unique_text": 400, "unique_labels": 7, "labels": { "6": { "count": 65 }, "1": { "count": 65 }, "4": { "count": 65 }, "7": { "count": 30 }, "3": { "count": 55 }, "0": { "count": 60 }, "2": { "count": 60 } } }, "rej": { "num_samples": 350, "number_of_characters": 245109, "number_texts_intersect_with_train": 0, "min_text_length": 502, "average_text_length": 700.3114285714286, "max_text_length": 1067, "unique_text": 350, "unique_labels": 8, "labels": { "0": { "count": 65 }, "5": { "count": 33 }, "1": { "count": 31 }, "6": { "count": 37 }, "4": { "count": 46 }, "2": { "count": 71 }, "7": { "count": 15 }, "3": { "count": 52 } } }, "sun": { "num_samples": 900, "number_of_characters": 688451, "number_texts_intersect_with_train": 0, "min_text_length": 543, "average_text_length": 764.9455555555555, "max_text_length": 1425, "unique_text": 900, "unique_labels": 8, "labels": { "5": { "count": 121 }, "4": { "count": 98 }, "6": { "count": 141 }, "3": { "count": 109 }, "7": { "count": 59 }, "1": { "count": 124 }, "2": { "count": 115 }, "0": { "count": 133 } } } } }, "train": { "num_samples": 15516, "number_of_characters": 11485555, "number_texts_intersect_with_train": null, "min_text_length": 504, "average_text_length": 740.2394302655324, "max_text_length": 2300, "unique_text": 15514, "unique_labels": 8, "labels": { "3": { "count": 1890 }, "4": { "count": 1664 }, "0": { "count": 2997 }, "5": { "count": 1511 }, "6": { "count": 1765 }, "2": { "count": 2350 }, "1": { "count": 2233 }, "7": { "count": 1106 } }, "hf_subset_descriptive_stats": { "btk": { "num_samples": 1350, "number_of_characters": 927651, "number_texts_intersect_with_train": null, "min_text_length": 504, "average_text_length": 687.1488888888889, "max_text_length": 2267, "unique_text": 1350, "unique_labels": 8, "labels": { "3": { "count": 176 }, "4": { "count": 152 }, "0": { "count": 288 }, "5": { "count": 129 }, "6": { "count": 124 }, "2": { "count": 209 }, "1": { "count": 184 }, "7": { "count": 88 } } }, "bew": { "num_samples": 2650, "number_of_characters": 2145717, "number_texts_intersect_with_train": null, "min_text_length": 565, "average_text_length": 809.7045283018867, "max_text_length": 2300, "unique_text": 2650, "unique_labels": 8, "labels": { "5": { "count": 308 }, "7": { "count": 178 }, "0": { "count": 482 }, "3": { "count": 331 }, "1": { "count": 399 }, "6": { "count": 299 }, "2": { "count": 341 }, "4": { "count": 312 } } }, "bug": { "num_samples": 93, "number_of_characters": 69528, "number_texts_intersect_with_train": null, "min_text_length": 608, "average_text_length": 747.6129032258065, "max_text_length": 965, "unique_text": 93, "unique_labels": 8, "labels": { "2": { "count": 7 }, "4": { "count": 5 }, "7": { "count": 10 }, "1": { "count": 12 }, "6": { "count": 4 }, "3": { "count": 20 }, "5": { "count": 15 }, "0": { "count": 20 } } }, "jav": { "num_samples": 2650, "number_of_characters": 1841858, "number_texts_intersect_with_train": null, "min_text_length": 556, "average_text_length": 695.0407547169812, "max_text_length": 1354, "unique_text": 2650, "unique_labels": 8, "labels": { "5": { "count": 337 }, "0": { "count": 416 }, "1": { "count": 338 }, "3": { "count": 337 }, "4": { "count": 343 }, "6": { "count": 328 }, "2": { "count": 372 }, "7": { "count": 179 } } }, "mad": { "num_samples": 1800, "number_of_characters": 1293049, "number_texts_intersect_with_train": null, "min_text_length": 566, "average_text_length": 718.3605555555556, "max_text_length": 1157, "unique_text": 1800, "unique_labels": 8, "labels": { "0": { "count": 483 }, "3": { "count": 182 }, "2": { "count": 303 }, "1": { "count": 303 }, "6": { "count": 204 }, "5": { "count": 67 }, "4": { "count": 130 }, "7": { "count": 128 } } }, "mak": { "num_samples": 1500, "number_of_characters": 1084894, "number_texts_intersect_with_train": null, "min_text_length": 504, "average_text_length": 723.2626666666666, "max_text_length": 1187, "unique_text": 1500, "unique_labels": 8, "labels": { "0": { "count": 332 }, "7": { "count": 111 }, "3": { "count": 223 }, "2": { "count": 247 }, "1": { "count": 226 }, "4": { "count": 159 }, "6": { "count": 146 }, "5": { "count": 56 } } }, "min": { "num_samples": 2400, "number_of_characters": 1766506, "number_texts_intersect_with_train": null, "min_text_length": 520, "average_text_length": 736.0441666666667, "max_text_length": 1300, "unique_text": 2398, "unique_labels": 8, "labels": { "1": { "count": 361 }, "4": { "count": 193 }, "7": { "count": 169 }, "2": { "count": 415 }, "6": { "count": 238 }, "0": { "count": 540 }, "3": { "count": 231 }, "5": { "count": 253 } } }, "mui": { "num_samples": 168, "number_of_characters": 133585, "number_texts_intersect_with_train": null, "min_text_length": 616, "average_text_length": 795.1488095238095, "max_text_length": 1663, "unique_text": 168, "unique_labels": 7, "labels": { "3": { "count": 36 }, "0": { "count": 29 }, "6": { "count": 27 }, "2": { "count": 26 }, "1": { "count": 20 }, "4": { "count": 21 }, "7": { "count": 9 } } }, "rej": { "num_samples": 105, "number_of_characters": 72800, "number_texts_intersect_with_train": null, "min_text_length": 539, "average_text_length": 693.3333333333334, "max_text_length": 935, "unique_text": 105, "unique_labels": 8, "labels": { "3": { "count": 14 }, "0": { "count": 19 }, "5": { "count": 13 }, "4": { "count": 13 }, "1": { "count": 12 }, "2": { "count": 21 }, "6": { "count": 8 }, "7": { "count": 5 } } }, "sun": { "num_samples": 2800, "number_of_characters": 2149967, "number_texts_intersect_with_train": null, "min_text_length": 562, "average_text_length": 767.8453571428571, "max_text_length": 1764, "unique_text": 2800, "unique_labels": 8, "labels": { "0": { "count": 388 }, "7": { "count": 229 }, "4": { "count": 336 }, "3": { "count": 340 }, "1": { "count": 378 }, "5": { "count": 333 }, "6": { "count": 387 }, "2": { "count": 409 } } } } } } ```
--- *This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*