--- 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: [] dataset_info: - config_name: bew features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 2185124 num_examples: 2698 - name: validation num_bytes: 353563 num_examples: 430 - name: test num_bytes: 646240 num_examples: 800 download_size: 1925803 dataset_size: 3184927 - config_name: btk features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 799635 num_examples: 1149 - name: validation num_bytes: 201035 num_examples: 292 - name: test num_bytes: 345218 num_examples: 500 download_size: 806158 dataset_size: 1345888 - config_name: bug features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 67939 num_examples: 87 - name: validation num_bytes: 38946 num_examples: 50 - name: test num_bytes: 238564 num_examples: 300 download_size: 210832 dataset_size: 345449 - config_name: jav features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 1953278 num_examples: 2800 - name: validation num_bytes: 309172 num_examples: 440 - name: test num_bytes: 558183 num_examples: 800 download_size: 1637364 dataset_size: 2820633 - config_name: mad features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 718438 num_examples: 999 - name: validation num_bytes: 188269 num_examples: 263 - name: test num_bytes: 359056 num_examples: 500 download_size: 774503 dataset_size: 1265763 - config_name: mak features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 1084770 num_examples: 1499 - name: validation num_bytes: 223128 num_examples: 304 - name: test num_bytes: 360338 num_examples: 500 download_size: 997065 dataset_size: 1668236 - config_name: min features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 1497274 num_examples: 1996 - name: validation num_bytes: 264261 num_examples: 357 - name: test num_bytes: 600012 num_examples: 800 download_size: 1355069 dataset_size: 2361547 - config_name: mui features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 164859 num_examples: 201 - name: validation num_bytes: 62985 num_examples: 75 - name: test num_bytes: 327059 num_examples: 400 download_size: 329620 dataset_size: 554903 - config_name: rej features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 105377 num_examples: 136 - name: validation num_bytes: 37786 num_examples: 50 - name: test num_bytes: 237603 num_examples: 300 download_size: 213553 dataset_size: 380766 - config_name: sun features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 1854384 num_examples: 2398 - name: validation num_bytes: 315336 num_examples: 400 - name: test num_bytes: 621586 num_examples: 800 download_size: 1658848 dataset_size: 2791306 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 ---

NusaParagraphEmotionClassification

An MTEB dataset
Massive Text Embedding Benchmark
NusaParagraphEmotionClassification is a multi-class emotion classification on 10 Indonesian languages from the NusaParagraph dataset. | | | |---------------|---------------------------------------------| | 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(["NusaParagraphEmotionClassification"]) 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("NusaParagraphEmotionClassification") desc_stats = task.metadata.descriptive_stats ``` ```json { "test": { "num_samples": 5700, "number_of_characters": 4194411, "number_texts_intersect_with_train": 9, "min_text_length": 495, "average_text_length": 735.8615789473685, "max_text_length": 1842, "unique_text": 5697, "unique_labels": 7, "labels": { "4": { "count": 649 }, "5": { "count": 687 }, "3": { "count": 896 }, "0": { "count": 1518 }, "6": { "count": 496 }, "2": { "count": 778 }, "1": { "count": 676 } }, "hf_subset_descriptive_stats": { "btk": { "num_samples": 500, "number_of_characters": 339185, "number_texts_intersect_with_train": 4, "min_text_length": 495, "average_text_length": 678.37, "max_text_length": 1808, "unique_text": 499, "unique_labels": 7, "labels": { "4": { "count": 58 }, "5": { "count": 71 }, "3": { "count": 84 }, "0": { "count": 103 }, "6": { "count": 51 }, "2": { "count": 73 }, "1": { "count": 60 } } }, "bew": { "num_samples": 800, "number_of_characters": 625862, "number_texts_intersect_with_train": 3, "min_text_length": 561, "average_text_length": 782.3275, "max_text_length": 1598, "unique_text": 798, "unique_labels": 7, "labels": { "0": { "count": 221 }, "5": { "count": 96 }, "6": { "count": 82 }, "1": { "count": 126 }, "3": { "count": 100 }, "4": { "count": 83 }, "2": { "count": 92 } } }, "bug": { "num_samples": 300, "number_of_characters": 234950, "number_texts_intersect_with_train": 0, "min_text_length": 583, "average_text_length": 783.1666666666666, "max_text_length": 1255, "unique_text": 300, "unique_labels": 7, "labels": { "0": { "count": 82 }, "4": { "count": 45 }, "3": { "count": 65 }, "5": { "count": 23 }, "1": { "count": 24 }, "6": { "count": 23 }, "2": { "count": 38 } } }, "jav": { "num_samples": 800, "number_of_characters": 548221, "number_texts_intersect_with_train": 0, "min_text_length": 564, "average_text_length": 685.27625, "max_text_length": 1106, "unique_text": 800, "unique_labels": 7, "labels": { "3": { "count": 101 }, "5": { "count": 87 }, "6": { "count": 90 }, "1": { "count": 93 }, "4": { "count": 102 }, "0": { "count": 222 }, "2": { "count": 105 } } }, "mad": { "num_samples": 500, "number_of_characters": 352867, "number_texts_intersect_with_train": 2, "min_text_length": 585, "average_text_length": 705.734, "max_text_length": 1260, "unique_text": 500, "unique_labels": 7, "labels": { "5": { "count": 49 }, "0": { "count": 163 }, "3": { "count": 110 }, "1": { "count": 28 }, "2": { "count": 96 }, "4": { "count": 51 }, "6": { "count": 3 } } }, "mak": { "num_samples": 500, "number_of_characters": 352366, "number_texts_intersect_with_train": 0, "min_text_length": 498, "average_text_length": 704.732, "max_text_length": 1096, "unique_text": 500, "unique_labels": 7, "labels": { "5": { "count": 78 }, "3": { "count": 110 }, "4": { "count": 69 }, "1": { "count": 44 }, "2": { "count": 71 }, "6": { "count": 25 }, "0": { "count": 103 } } }, "min": { "num_samples": 800, "number_of_characters": 590388, "number_texts_intersect_with_train": 0, "min_text_length": 558, "average_text_length": 737.985, "max_text_length": 1636, "unique_text": 800, "unique_labels": 7, "labels": { "6": { "count": 86 }, "1": { "count": 130 }, "0": { "count": 239 }, "5": { "count": 89 }, "3": { "count": 103 }, "4": { "count": 66 }, "2": { "count": 87 } } }, "mui": { "num_samples": 400, "number_of_characters": 322255, "number_texts_intersect_with_train": 0, "min_text_length": 590, "average_text_length": 805.6375, "max_text_length": 1352, "unique_text": 400, "unique_labels": 7, "labels": { "0": { "count": 117 }, "3": { "count": 58 }, "4": { "count": 61 }, "2": { "count": 57 }, "5": { "count": 58 }, "6": { "count": 18 }, "1": { "count": 31 } } }, "rej": { "num_samples": 300, "number_of_characters": 218191, "number_texts_intersect_with_train": 0, "min_text_length": 520, "average_text_length": 727.3033333333333, "max_text_length": 1187, "unique_text": 300, "unique_labels": 7, "labels": { "3": { "count": 60 }, "4": { "count": 26 }, "2": { "count": 62 }, "0": { "count": 59 }, "6": { "count": 26 }, "1": { "count": 35 }, "5": { "count": 32 } } }, "sun": { "num_samples": 800, "number_of_characters": 610126, "number_texts_intersect_with_train": 0, "min_text_length": 564, "average_text_length": 762.6575, "max_text_length": 1842, "unique_text": 800, "unique_labels": 7, "labels": { "3": { "count": 105 }, "6": { "count": 92 }, "4": { "count": 88 }, "5": { "count": 104 }, "0": { "count": 209 }, "2": { "count": 97 }, "1": { "count": 105 } } } } }, "train": { "num_samples": 13963, "number_of_characters": 10210343, "number_texts_intersect_with_train": null, "min_text_length": 467, "average_text_length": 731.2427845018979, "max_text_length": 2156, "unique_text": 13959, "unique_labels": 7, "labels": { "6": { "count": 1343 }, "3": { "count": 2070 }, "5": { "count": 1686 }, "4": { "count": 1648 }, "0": { "count": 3609 }, "1": { "count": 1730 }, "2": { "count": 1877 } }, "hf_subset_descriptive_stats": { "btk": { "num_samples": 1149, "number_of_characters": 785657, "number_texts_intersect_with_train": null, "min_text_length": 467, "average_text_length": 683.7745865970409, "max_text_length": 1807, "unique_text": 1149, "unique_labels": 7, "labels": { "6": { "count": 107 }, "3": { "count": 186 }, "5": { "count": 145 }, "4": { "count": 141 }, "0": { "count": 259 }, "1": { "count": 155 }, "2": { "count": 156 } } }, "bew": { "num_samples": 2698, "number_of_characters": 2120349, "number_texts_intersect_with_train": null, "min_text_length": 535, "average_text_length": 785.896590066716, "max_text_length": 1715, "unique_text": 2694, "unique_labels": 7, "labels": { "3": { "count": 319 }, "5": { "count": 279 }, "6": { "count": 307 }, "0": { "count": 744 }, "1": { "count": 399 }, "2": { "count": 347 }, "4": { "count": 303 } } }, "bug": { "num_samples": 87, "number_of_characters": 66895, "number_texts_intersect_with_train": null, "min_text_length": 622, "average_text_length": 768.9080459770115, "max_text_length": 1150, "unique_text": 87, "unique_labels": 7, "labels": { "1": { "count": 11 }, "5": { "count": 7 }, "0": { "count": 25 }, "2": { "count": 8 }, "3": { "count": 21 }, "4": { "count": 11 }, "6": { "count": 4 } } }, "jav": { "num_samples": 2800, "number_of_characters": 1918633, "number_texts_intersect_with_train": null, "min_text_length": 562, "average_text_length": 685.2260714285715, "max_text_length": 1405, "unique_text": 2800, "unique_labels": 7, "labels": { "5": { "count": 348 }, "1": { "count": 340 }, "0": { "count": 678 }, "3": { "count": 369 }, "4": { "count": 362 }, "6": { "count": 354 }, "2": { "count": 349 } } }, "mad": { "num_samples": 999, "number_of_characters": 705416, "number_texts_intersect_with_train": null, "min_text_length": 564, "average_text_length": 706.1221221221222, "max_text_length": 2156, "unique_text": 999, "unique_labels": 7, "labels": { "5": { "count": 100 }, "0": { "count": 335 }, "2": { "count": 185 }, "3": { "count": 205 }, "4": { "count": 117 }, "1": { "count": 49 }, "6": { "count": 8 } } }, "mak": { "num_samples": 1499, "number_of_characters": 1061229, "number_texts_intersect_with_train": null, "min_text_length": 484, "average_text_length": 707.9579719813208, "max_text_length": 1168, "unique_text": 1499, "unique_labels": 7, "labels": { "3": { "count": 324 }, "4": { "count": 189 }, "2": { "count": 237 }, "0": { "count": 304 }, "1": { "count": 127 }, "6": { "count": 81 }, "5": { "count": 237 } } }, "min": { "num_samples": 1996, "number_of_characters": 1473263, "number_texts_intersect_with_train": null, "min_text_length": 543, "average_text_length": 738.1077154308617, "max_text_length": 1321, "unique_text": 1996, "unique_labels": 7, "labels": { "0": { "count": 537 }, "6": { "count": 230 }, "4": { "count": 178 }, "2": { "count": 240 }, "1": { "count": 317 }, "3": { "count": 301 }, "5": { "count": 193 } } }, "mui": { "num_samples": 201, "number_of_characters": 162437, "number_texts_intersect_with_train": null, "min_text_length": 623, "average_text_length": 808.1442786069651, "max_text_length": 1404, "unique_text": 201, "unique_labels": 7, "labels": { "0": { "count": 62 }, "5": { "count": 32 }, "3": { "count": 23 }, "1": { "count": 17 }, "2": { "count": 31 }, "4": { "count": 31 }, "6": { "count": 5 } } }, "rej": { "num_samples": 136, "number_of_characters": 96411, "number_texts_intersect_with_train": null, "min_text_length": 528, "average_text_length": 708.9044117647059, "max_text_length": 1138, "unique_text": 136, "unique_labels": 7, "labels": { "0": { "count": 29 }, "3": { "count": 26 }, "2": { "count": 27 }, "1": { "count": 12 }, "5": { "count": 10 }, "4": { "count": 20 }, "6": { "count": 12 } } }, "sun": { "num_samples": 2398, "number_of_characters": 1820053, "number_texts_intersect_with_train": null, "min_text_length": 558, "average_text_length": 758.987906588824, "max_text_length": 1546, "unique_text": 2398, "unique_labels": 7, "labels": { "1": { "count": 303 }, "4": { "count": 296 }, "0": { "count": 636 }, "2": { "count": 297 }, "3": { "count": 296 }, "6": { "count": 235 }, "5": { "count": 335 } } } } } } ```
--- *This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*