--- annotations_creators: - human-annotated language: - cmn - deu - eng - fra - jpn - spa license: other multilinguality: multilingual task_categories: - text-classification task_ids: [] dataset_info: - config_name: de features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 49404539 num_examples: 200000 - name: validation num_bytes: 1228543 num_examples: 5000 - name: test num_bytes: 1233991 num_examples: 5000 download_size: 31735470 dataset_size: 51867073 - config_name: en features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 43524802 num_examples: 200000 - name: validation num_bytes: 1097465 num_examples: 5000 - name: test num_bytes: 1083550 num_examples: 5000 download_size: 27948523 dataset_size: 45705817 - config_name: es features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 37372261 num_examples: 200000 - name: validation num_bytes: 928778 num_examples: 5000 - name: test num_bytes: 937306 num_examples: 5000 download_size: 24055031 dataset_size: 39238345 - config_name: fr features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 39570631 num_examples: 200000 - name: validation num_bytes: 964810 num_examples: 5000 - name: test num_bytes: 989048 num_examples: 5000 download_size: 25171138 dataset_size: 41524489 - config_name: ja features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 67483811 num_examples: 200000 - name: validation num_bytes: 1662207 num_examples: 5000 - name: test num_bytes: 1675094 num_examples: 5000 download_size: 40906746 dataset_size: 70821112 - config_name: zh features: - name: text dtype: string - name: label dtype: int64 splits: - name: train num_bytes: 37043208 num_examples: 200000 - name: validation num_bytes: 914709 num_examples: 5000 - name: test num_bytes: 930258 num_examples: 5000 download_size: 26125561 dataset_size: 38888175 configs: - config_name: de data_files: - split: train path: de/train-* - split: validation path: de/validation-* - split: test path: de/test-* - config_name: en data_files: - split: train path: en/train-* - split: validation path: en/validation-* - split: test path: en/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: ja data_files: - split: train path: ja/train-* - split: validation path: ja/validation-* - split: test path: ja/test-* - config_name: zh data_files: - split: train path: zh/train-* - split: validation path: zh/validation-* - split: test path: zh/test-* tags: - mteb - text ---

AmazonReviewsClassification

An MTEB dataset
Massive Text Embedding Benchmark
A collection of Amazon reviews specifically designed to aid research in multilingual text classification. | | | |---------------|---------------------------------------------| | Task category | t2c | | Domains | Reviews, Written | | Reference | https://arxiv.org/abs/2010.02573 | ## 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(["AmazonReviewsClassification"]) 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 @misc{keung2020multilingual, archiveprefix = {arXiv}, author = {Phillip Keung and Yichao Lu and György Szarvas and Noah A. Smith}, eprint = {2010.02573}, primaryclass = {cs.CL}, title = {The Multilingual Amazon Reviews 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("AmazonReviewsClassification") desc_stats = task.metadata.descriptive_stats ``` ```json { "validation": { "num_samples": 30000, "number_of_characters": 4776902, "number_texts_intersect_with_train": 155, "min_text_length": 20, "average_text_length": 159.23006666666666, "max_text_length": 3722, "unique_text": 29997, "unique_labels": 5, "labels": { "0": { "count": 6000 }, "1": { "count": 6000 }, "2": { "count": 6000 }, "3": { "count": 6000 }, "4": { "count": 6000 } }, "hf_subset_descriptive_stats": { "en": { "num_samples": 5000, "number_of_characters": 1034433, "number_texts_intersect_with_train": 5, "min_text_length": 24, "average_text_length": 206.8866, "max_text_length": 3722, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "de": { "num_samples": 5000, "number_of_characters": 1152232, "number_texts_intersect_with_train": 8, "min_text_length": 24, "average_text_length": 230.4464, "max_text_length": 1596, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "es": { "num_samples": 5000, "number_of_characters": 857010, "number_texts_intersect_with_train": 10, "min_text_length": 24, "average_text_length": 171.402, "max_text_length": 1618, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "fr": { "num_samples": 5000, "number_of_characters": 878607, "number_texts_intersect_with_train": 13, "min_text_length": 23, "average_text_length": 175.7214, "max_text_length": 1626, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "ja": { "num_samples": 5000, "number_of_characters": 555716, "number_texts_intersect_with_train": 9, "min_text_length": 20, "average_text_length": 111.1432, "max_text_length": 1233, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "zh": { "num_samples": 5000, "number_of_characters": 298904, "number_texts_intersect_with_train": 110, "min_text_length": 21, "average_text_length": 59.7808, "max_text_length": 1388, "unique_text": 4997, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } } } }, "test": { "num_samples": 30000, "number_of_characters": 4810650, "number_texts_intersect_with_train": 134, "min_text_length": 19, "average_text_length": 160.355, "max_text_length": 3814, "unique_text": 30000, "unique_labels": 5, "labels": { "0": { "count": 6000 }, "1": { "count": 6000 }, "2": { "count": 6000 }, "3": { "count": 6000 }, "4": { "count": 6000 } }, "hf_subset_descriptive_stats": { "en": { "num_samples": 5000, "number_of_characters": 1020794, "number_texts_intersect_with_train": 2, "min_text_length": 24, "average_text_length": 204.1588, "max_text_length": 2397, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "de": { "num_samples": 5000, "number_of_characters": 1157422, "number_texts_intersect_with_train": 7, "min_text_length": 25, "average_text_length": 231.4844, "max_text_length": 3814, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "es": { "num_samples": 5000, "number_of_characters": 865393, "number_texts_intersect_with_train": 12, "min_text_length": 24, "average_text_length": 173.0786, "max_text_length": 1818, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "fr": { "num_samples": 5000, "number_of_characters": 902601, "number_texts_intersect_with_train": 14, "min_text_length": 22, "average_text_length": 180.5202, "max_text_length": 3800, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "ja": { "num_samples": 5000, "number_of_characters": 560191, "number_texts_intersect_with_train": 5, "min_text_length": 22, "average_text_length": 112.0382, "max_text_length": 1054, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } }, "zh": { "num_samples": 5000, "number_of_characters": 304249, "number_texts_intersect_with_train": 94, "min_text_length": 19, "average_text_length": 60.8498, "max_text_length": 837, "unique_text": 5000, "unique_labels": 5, "labels": { "0": { "count": 1000 }, "1": { "count": 1000 }, "2": { "count": 1000 }, "3": { "count": 1000 }, "4": { "count": 1000 } } } } }, "train": { "num_samples": 1200000, "number_of_characters": 192628074, "number_texts_intersect_with_train": null, "min_text_length": 15, "average_text_length": 160.523395, "max_text_length": 3931, "unique_text": 1196369, "unique_labels": 5, "labels": { "0": { "count": 240000 }, "1": { "count": 240000 }, "2": { "count": 240000 }, "3": { "count": 240000 }, "4": { "count": 240000 } }, "hf_subset_descriptive_stats": { "en": { "num_samples": 200000, "number_of_characters": 41010127, "number_texts_intersect_with_train": null, "min_text_length": 18, "average_text_length": 205.050635, "max_text_length": 3931, "unique_text": 199891, "unique_labels": 5, "labels": { "0": { "count": 40000 }, "1": { "count": 40000 }, "2": { "count": 40000 }, "3": { "count": 40000 }, "4": { "count": 40000 } } }, "de": { "num_samples": 200000, "number_of_characters": 46342647, "number_texts_intersect_with_train": null, "min_text_length": 21, "average_text_length": 231.713235, "max_text_length": 3874, "unique_text": 199877, "unique_labels": 5, "labels": { "0": { "count": 40000 }, "1": { "count": 40000 }, "2": { "count": 40000 }, "3": { "count": 40000 }, "4": { "count": 40000 } } }, "es": { "num_samples": 200000, "number_of_characters": 34494548, "number_texts_intersect_with_train": null, "min_text_length": 22, "average_text_length": 172.47274, "max_text_length": 3162, "unique_text": 199726, "unique_labels": 5, "labels": { "0": { "count": 40000 }, "1": { "count": 40000 }, "2": { "count": 40000 }, "3": { "count": 40000 }, "4": { "count": 40000 } } }, "fr": { "num_samples": 200000, "number_of_characters": 36091159, "number_texts_intersect_with_train": null, "min_text_length": 19, "average_text_length": 180.455795, "max_text_length": 3917, "unique_text": 199612, "unique_labels": 5, "labels": { "0": { "count": 40000 }, "1": { "count": 40000 }, "2": { "count": 40000 }, "3": { "count": 40000 }, "4": { "count": 40000 } } }, "ja": { "num_samples": 200000, "number_of_characters": 22575204, "number_texts_intersect_with_train": null, "min_text_length": 16, "average_text_length": 112.87602, "max_text_length": 1466, "unique_text": 199845, "unique_labels": 5, "labels": { "0": { "count": 40000 }, "1": { "count": 40000 }, "2": { "count": 40000 }, "3": { "count": 40000 }, "4": { "count": 40000 } } }, "zh": { "num_samples": 200000, "number_of_characters": 12114389, "number_texts_intersect_with_train": null, "min_text_length": 15, "average_text_length": 60.571945, "max_text_length": 2423, "unique_text": 197418, "unique_labels": 5, "labels": { "0": { "count": 40000 }, "1": { "count": 40000 }, "2": { "count": 40000 }, "3": { "count": 40000 }, "4": { "count": 40000 } } } } } } ```
--- *This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*