mteb/StackOverflowDupQuestions

1---2annotations_creators:3- derived4language:5- eng6license: cc-by-nc-sa-4.07multilinguality: monolingual8task_categories:9- text-ranking10task_ids:11- multiple-choice-qa12dataset_info:13- config_name: corpus14  features:15  - name: _id16    dtype: string17  - name: text18    dtype: string19  - name: title20    dtype: string21  splits:22  - name: train23    num_bytes: 5152569624    num_examples: 59352225  - name: test26    num_bytes: 761885127    num_examples: 8947028  download_size: 2164999029  dataset_size: 5914454730- config_name: default31  features:32  - name: query-id33    dtype: string34  - name: corpus-id35    dtype: string36  - name: score37    dtype: int6438  splits:39  - name: train40    num_bytes: 3675040241    num_examples: 59352242  - name: test43    num_bytes: 521583944    num_examples: 8947045  download_size: 456262646  dataset_size: 4196624147- config_name: queries48  features:49  - name: _id50    dtype: string51  - name: text52    dtype: string53  splits:54  - name: train55    num_bytes: 151366556    num_examples: 1984757  - name: test58    num_bytes: 22379659    num_examples: 299260  download_size: 100637161  dataset_size: 173746162- config_name: top_ranked63  features:64  - name: query-id65    dtype: string66  - name: corpus-ids67    sequence: string68  splits:69  - name: train70    num_bytes: 2092925571    num_examples: 1984772  - name: test73    num_bytes: 298751274    num_examples: 299275  download_size: 447205576  dataset_size: 2391676777configs:78- config_name: corpus79  data_files:80  - split: train81    path: corpus/train-*82  - split: test83    path: corpus/test-*84- config_name: default85  data_files:86  - split: train87    path: data/train-*88  - split: test89    path: data/test-*90- config_name: queries91  data_files:92  - split: train93    path: queries/train-*94  - split: test95    path: queries/test-*96- config_name: top_ranked97  data_files:98  - split: train99    path: top_ranked/train-*100  - split: test101    path: top_ranked/test-*102tags:103- mteb104- text105---106<!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->107 108<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;">109  <h1 style="font-size: 3.5rem; color: #1a1a1a; margin: 0 0 20px 0; letter-spacing: 2px; font-weight: 700;">StackOverflowDupQuestions</h1>110  <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>111  <div style="font-size: 0.9rem; color: #2c5282; margin-top: 10px;">Massive Text Embedding Benchmark</div>112</div>113 114Stack Overflow Duplicate Questions Task for questions with the tags Java, JavaScript and Python115 116|               |                                             |117|---------------|---------------------------------------------|118| Task category | t2t                              |119| Domains       | Written, Blog, Programming                               |120| Reference     | https://www.microsoft.com/en-us/research/uploads/prod/2019/03/nl4se18LinkSO.pdf |121 122 123## How to evaluate on this task124 125You can evaluate an embedding model on this dataset using the following code:126 127```python128import mteb129 130task = mteb.get_tasks(["StackOverflowDupQuestions"])131evaluator = mteb.MTEB(task)132 133model = mteb.get_model(YOUR_MODEL)134evaluator.run(model)135```136 137<!-- Datasets want link to arxiv in readme to autolink dataset with paper -->138To learn more about how to run models on `mteb` task check out the [GitHub repitory](https://github.com/embeddings-benchmark/mteb). 139 140## Citation141 142If 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).143 144```bibtex145 146@article{Liu2018LinkSOAD,147  author = {Xueqing Liu and Chi Wang and Yue Leng and ChengXiang Zhai},148  journal = {Proceedings of the 4th ACM SIGSOFT International Workshop on NLP for Software Engineering},149  title = {LinkSO: a dataset for learning to retrieve similar question answer pairs on software development forums},150  url = {https://api.semanticscholar.org/CorpusID:53111679},151  year = {2018},152}153 154 155@article{enevoldsen2025mmtebmassivemultilingualtext,156  title={MMTEB: Massive Multilingual Text Embedding Benchmark},157  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},158  publisher = {arXiv},159  journal={arXiv preprint arXiv:2502.13595},160  year={2025},161  url={https://arxiv.org/abs/2502.13595},162  doi = {10.48550/arXiv.2502.13595},163}164 165@article{muennighoff2022mteb,166  author = {Muennighoff, Niklas and Tazi, Nouamane and Magne, Lo{\"\i}c and Reimers, Nils},167  title = {MTEB: Massive Text Embedding Benchmark},168  publisher = {arXiv},169  journal={arXiv preprint arXiv:2210.07316},170  year = {2022}171  url = {https://arxiv.org/abs/2210.07316},172  doi = {10.48550/ARXIV.2210.07316},173}174```175 176# Dataset Statistics177<details>178  <summary> Dataset Statistics</summary>179 180The following code contains the descriptive statistics from the task. These can also be obtained using:181 182```python183import mteb184 185task = mteb.get_task("StackOverflowDupQuestions")186 187desc_stats = task.metadata.descriptive_stats188```189 190```json191{192    "test": {193        "num_samples": 92462,194        "number_of_characters": 4138870,195        "num_documents": 89470,196        "min_document_length": 10,197        "average_document_length": 44.482094556834696,198        "max_document_length": 150,199        "unique_documents": 89470,200        "num_queries": 2992,201        "min_query_length": 13,202        "average_query_length": 53.160762032085564,203        "max_query_length": 149,204        "unique_queries": 2992,205        "none_queries": 0,206        "num_relevant_docs": 89470,207        "min_relevant_docs_per_query": 20,208        "average_relevant_docs_per_query": 1.1587566844919786,209        "max_relevant_docs_per_query": 30,210        "unique_relevant_docs": 89470,211        "num_instructions": null,212        "min_instruction_length": null,213        "average_instruction_length": null,214        "max_instruction_length": null,215        "unique_instructions": null,216        "num_top_ranked": 2992,217        "min_top_ranked_per_query": 20,218        "average_top_ranked_per_query": 29.90307486631016,219        "max_top_ranked_per_query": 30220    }221}222```223 224</details>225 226---227*This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*