mteb/CQADupstack-Programmers-PL

1---2annotations_creators:3- derived4language:5- pol6license: unknown7multilinguality: translated8source_datasets:9- mteb/cqadupstack-programmers10task_categories:11- text-retrieval12task_ids: []13dataset_info:14- config_name: corpus15  features:16  - name: _id17    dtype: string18  - name: text19    dtype: string20  - name: title21    dtype: string22  splits:23  - name: test24    num_bytes: 3715036625    num_examples: 3217626  download_size: 2296709627  dataset_size: 3715036628- config_name: default29  features:30  - name: query-id31    dtype: string32  - name: corpus-id33    dtype: string34  - name: score35    dtype: int6436  splits:37  - name: test38    num_bytes: 4545239    num_examples: 167540  download_size: 2263241  dataset_size: 4545242- config_name: queries43  features:44  - name: _id45    dtype: string46  - name: text47    dtype: string48  splits:49  - name: test50    num_bytes: 6789851    num_examples: 87652  download_size: 4590953  dataset_size: 6789854configs:55- config_name: corpus56  data_files:57  - split: test58    path: corpus/test-*59- config_name: default60  data_files:61  - split: test62    path: data/test-*63- config_name: queries64  data_files:65  - split: test66    path: queries/test-*67tags:68- mteb69- text70---71<!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->72 73<div align="center" style="padding: 40px 20px; background-color: white; border-radius: 12px; box-shadow: 0 2px 10px rgba(0, 0, 0, 0.05); max-width: 600px; margin: 0 auto;">74  <h1 style="font-size: 3.5rem; color: #1a1a1a; margin: 0 0 20px 0; letter-spacing: 2px; font-weight: 700;">CQADupstack-Programmers-PL</h1>75  <div style="font-size: 1.5rem; color: #4a4a4a; margin-bottom: 5px; font-weight: 300;">An <a href="https://github.com/embeddings-benchmark/mteb" style="color: #2c5282; font-weight: 600; text-decoration: none;" onmouseover="this.style.textDecoration='underline'" onmouseout="this.style.textDecoration='none'">MTEB</a> dataset</div>76  <div style="font-size: 0.9rem; color: #2c5282; margin-top: 10px;">Massive Text Embedding Benchmark</div>77</div>78 79CQADupStack: A Stack Exchange Question Duplicate Pairs Dataset80 81|               |                                             |82|---------------|---------------------------------------------|83| Task category | t2t                              |84| Domains       | Programming, Written, Non-fiction                               |85| Reference     | https://huggingface.co/datasets/clarin-knext/cqadupstack-programmers-pl |86 87 88## How to evaluate on this task89 90You can evaluate an embedding model on this dataset using the following code:91 92```python93import mteb94 95task = mteb.get_tasks(["CQADupstack-Programmers-PL"])96evaluator = mteb.MTEB(task)97 98model = mteb.get_model(YOUR_MODEL)99evaluator.run(model)100```101 102<!-- Datasets want link to arxiv in readme to autolink dataset with paper -->103To learn more about how to run models on `mteb` task check out the [GitHub repitory](https://github.com/embeddings-benchmark/mteb). 104 105## Citation106 107If 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).108 109```bibtex110 111@misc{wojtasik2024beirpl,112  archiveprefix = {arXiv},113  author = {Konrad Wojtasik and Vadim Shishkin and Kacper Wołowiec and Arkadiusz Janz and Maciej Piasecki},114  eprint = {2305.19840},115  primaryclass = {cs.IR},116  title = {BEIR-PL: Zero Shot Information Retrieval Benchmark for the Polish Language},117  year = {2024},118}119 120 121@article{enevoldsen2025mmtebmassivemultilingualtext,122  title={MMTEB: Massive Multilingual Text Embedding Benchmark},123  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},124  publisher = {arXiv},125  journal={arXiv preprint arXiv:2502.13595},126  year={2025},127  url={https://arxiv.org/abs/2502.13595},128  doi = {10.48550/arXiv.2502.13595},129}130 131@article{muennighoff2022mteb,132  author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Lo{\"\i}c and Reimers, Nils},133  title = {MTEB: Massive Text Embedding Benchmark},134  publisher = {arXiv},135  journal={arXiv preprint arXiv:2210.07316},136  year = {2022}137  url = {https://arxiv.org/abs/2210.07316},138  doi = {10.48550/ARXIV.2210.07316},139}140```141 142# Dataset Statistics143<details>144  <summary> Dataset Statistics</summary>145 146The following code contains the descriptive statistics from the task. These can also be obtained using:147 148```python149import mteb150 151task = mteb.get_task("CQADupstack-Programmers-PL")152 153desc_stats = task.metadata.descriptive_stats154```155 156```json157{158    "test": {159        "num_samples": 33052,160        "number_of_characters": 34685073,161        "num_documents": 32176,162        "min_document_length": 69,163        "average_document_length": 1076.326734211835,164        "max_document_length": 17795,165        "unique_documents": 32176,166        "num_queries": 876,167        "min_query_length": 10,168        "average_query_length": 60.71232876712329,169        "max_query_length": 160,170        "unique_queries": 876,171        "none_queries": 0,172        "num_relevant_docs": 1675,173        "min_relevant_docs_per_query": 1,174        "average_relevant_docs_per_query": 1.9121004566210045,175        "max_relevant_docs_per_query": 149,176        "unique_relevant_docs": 1675,177        "num_instructions": null,178        "min_instruction_length": null,179        "average_instruction_length": null,180        "max_instruction_length": null,181        "unique_instructions": null,182        "num_top_ranked": null,183        "min_top_ranked_per_query": null,184        "average_top_ranked_per_query": null,185        "max_top_ranked_per_query": null186    }187}188```189 190</details>191 192---193*This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*