--- annotations_creators: - expert-annotated language: - asm - ben - bho - ell - guj - kan - mar - ory - pan - rus - san - tam - tur license: unknown multilinguality: translated task_categories: - text-classification task_ids: - semantic-similarity-classification tags: - mteb - text dataset_info: - config_name: assamese features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 565556 num_examples: 1365 download_size: 230705 dataset_size: 565556 - config_name: bengali features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 567227 num_examples: 1365 download_size: 223053 dataset_size: 567227 - config_name: bhojpuri features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 549145 num_examples: 1365 download_size: 220031 dataset_size: 549145 - config_name: greek features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 446843 num_examples: 1365 download_size: 224614 dataset_size: 446843 - config_name: gujrati features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 550823 num_examples: 1365 download_size: 224504 dataset_size: 550823 - config_name: kannada features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 622208 num_examples: 1365 download_size: 239158 dataset_size: 622208 - config_name: marathi features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 569028 num_examples: 1365 download_size: 225578 dataset_size: 569028 - config_name: odiya features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 571151 num_examples: 1365 download_size: 228006 dataset_size: 571151 - config_name: punjabi features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 565812 num_examples: 1365 download_size: 224326 dataset_size: 565812 - config_name: russian features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 418863 num_examples: 1365 download_size: 213532 dataset_size: 418863 - config_name: sanskrit features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 598335 num_examples: 1365 download_size: 235984 dataset_size: 598335 - config_name: tamil features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 676943 num_examples: 1365 download_size: 245022 dataset_size: 676943 - config_name: turkish features: - name: sentence1 dtype: string - name: sentence2 dtype: string - name: labels dtype: int64 splits: - name: test num_bytes: 246707 num_examples: 1365 download_size: 156292 dataset_size: 246707 configs: - config_name: assamese data_files: - split: test path: assamese/test-* - config_name: bengali data_files: - split: test path: bengali/test-* - config_name: bhojpuri data_files: - split: test path: bhojpuri/test-* - config_name: greek data_files: - split: test path: greek/test-* - config_name: gujrati data_files: - split: test path: gujrati/test-* - config_name: kannada data_files: - split: test path: kannada/test-* - config_name: marathi data_files: - split: test path: marathi/test-* - config_name: odiya data_files: - split: test path: odiya/test-* - config_name: punjabi data_files: - split: test path: punjabi/test-* - config_name: russian data_files: - split: test path: russian/test-* - config_name: sanskrit data_files: - split: test path: sanskrit/test-* - config_name: tamil data_files: - split: test path: tamil/test-* - config_name: turkish data_files: - split: test path: turkish/test-* ---

XNLIV2

An MTEB dataset
Massive Text Embedding Benchmark
This is subset of 'XNLI 2.0: Improving XNLI dataset and performance on Cross Lingual Understanding' with languages that were not part of the original XNLI plus three (verified) languages that are not strongly covered in MTEB | | | |---------------|---------------------------------------------| | Task category | t2t | | Domains | Non-fiction, Fiction, Government, Written | | Reference | https://arxiv.org/pdf/2301.06527 | ## 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(["XNLIV2"]) 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{upadhyay2023xnli, author = {Upadhyay, Ankit Kumar and Upadhya, Harsit Kumar}, booktitle = {2023 IEEE 8th International Conference for Convergence in Technology (I2CT)}, organization = {IEEE}, pages = {1--6}, title = {XNLI 2.0: Improving XNLI dataset and performance on Cross Lingual Understanding (XLU)}, 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("XNLIV2") desc_stats = task.metadata.descriptive_stats ``` ```json { "test": { "num_samples": 17745, "number_of_characters": 2778287, "unique_pairs": 17745, "min_sentence1_length": 5, "avg_sentence1_length": 105.99329388560157, "max_sentence1_length": 339, "unique_sentence1": 14234, "min_sentence2_length": 8, "avg_sentence2_length": 50.57402085094393, "max_sentence2_length": 162, "unique_sentence2": 17745, "unique_labels": 2, "labels": { "0": { "count": 8879 }, "1": { "count": 8866 } } } } ```
--- *This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*