README.md

---
annotations_creators:
- expert-annotated
language:
- ara
- cmn
- deu
- eng
- fra
- ita
- jpn
- kor
- nld
- ron
license: cc-by-nc-nd-4.0
multilinguality: multilingual
task_categories:
- translation
task_ids: []
dataset_info:
- config_name: ar-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 241206
    num_examples: 888
  download_size: 140326
  dataset_size: 241206
- config_name: de-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 210975
    num_examples: 888
  download_size: 132175
  dataset_size: 210975
- config_name: en-ar
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 241206
    num_examples: 888
  download_size: 140326
  dataset_size: 241206
- config_name: en-de
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 210975
    num_examples: 888
  download_size: 132175
  dataset_size: 210975
- config_name: en-fr
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 207579
    num_examples: 890
  download_size: 129502
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- config_name: en-it
  features:
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  - name: sentence2
    dtype: string
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    num_examples: 929
  download_size: 127687
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- config_name: en-ja
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
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    num_examples: 871
  download_size: 128549
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- config_name: en-ko
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
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    num_examples: 879
  download_size: 134436
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- config_name: en-nl
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
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    num_examples: 1003
  download_size: 128499
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- config_name: en-ro
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
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    num_examples: 914
  download_size: 131395
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- config_name: en-zh
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
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    num_examples: 879
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- config_name: fr-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 207579
    num_examples: 890
  download_size: 129502
  dataset_size: 207579
- config_name: it-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 200023
    num_examples: 929
  download_size: 127687
  dataset_size: 200023
- config_name: it-nl
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
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    num_examples: 1001
  download_size: 129302
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- config_name: it-ro
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 204989
    num_examples: 914
  download_size: 133564
  dataset_size: 204989
- config_name: ja-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 208124
    num_examples: 871
  download_size: 128549
  dataset_size: 208124
- config_name: ko-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 219295
    num_examples: 879
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  dataset_size: 219295
- config_name: nl-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 197814
    num_examples: 1003
  download_size: 128499
  dataset_size: 197814
- config_name: nl-it
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 197774
    num_examples: 1001
  download_size: 129302
  dataset_size: 197774
- config_name: nl-ro
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 202380
    num_examples: 913
  download_size: 131434
  dataset_size: 202380
- config_name: ro-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 205028
    num_examples: 914
  download_size: 131395
  dataset_size: 205028
- config_name: ro-it
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 204989
    num_examples: 914
  download_size: 133564
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- config_name: ro-nl
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
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  - name: validation
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- config_name: zh-en
  features:
  - name: sentence1
    dtype: string
  - name: sentence2
    dtype: string
  splits:
  - name: validation
    num_bytes: 202537
    num_examples: 879
  download_size: 128895
  dataset_size: 202537
configs:
- config_name: ar-en
  data_files:
  - split: validation
    path: ar-en/validation-*
- config_name: de-en
  data_files:
  - split: validation
    path: de-en/validation-*
- config_name: en-ar
  data_files:
  - split: validation
    path: en-ar/validation-*
- config_name: en-de
  data_files:
  - split: validation
    path: en-de/validation-*
- config_name: en-fr
  data_files:
  - split: validation
    path: en-fr/validation-*
- config_name: en-it
  data_files:
  - split: validation
    path: en-it/validation-*
- config_name: en-ja
  data_files:
  - split: validation
    path: en-ja/validation-*
- config_name: en-ko
  data_files:
  - split: validation
    path: en-ko/validation-*
- config_name: en-nl
  data_files:
  - split: validation
    path: en-nl/validation-*
- config_name: en-ro
  data_files:
  - split: validation
    path: en-ro/validation-*
- config_name: en-zh
  data_files:
  - split: validation
    path: en-zh/validation-*
- config_name: fr-en
  data_files:
  - split: validation
    path: fr-en/validation-*
- config_name: it-en
  data_files:
  - split: validation
    path: it-en/validation-*
- config_name: it-nl
  data_files:
  - split: validation
    path: it-nl/validation-*
- config_name: it-ro
  data_files:
  - split: validation
    path: it-ro/validation-*
- config_name: ja-en
  data_files:
  - split: validation
    path: ja-en/validation-*
- config_name: ko-en
  data_files:
  - split: validation
    path: ko-en/validation-*
- config_name: nl-en
  data_files:
  - split: validation
    path: nl-en/validation-*
- config_name: nl-it
  data_files:
  - split: validation
    path: nl-it/validation-*
- config_name: nl-ro
  data_files:
  - split: validation
    path: nl-ro/validation-*
- config_name: ro-en
  data_files:
  - split: validation
    path: ro-en/validation-*
- config_name: ro-it
  data_files:
  - split: validation
    path: ro-it/validation-*
- config_name: ro-nl
  data_files:
  - split: validation
    path: ro-nl/validation-*
- config_name: zh-en
  data_files:
  - split: validation
    path: zh-en/validation-*
tags:
- mteb
- text
---
<!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->

<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;">
  <h1 style="font-size: 3.5rem; color: #1a1a1a; margin: 0 0 20px 0; letter-spacing: 2px; font-weight: 700;">IWSLT2017BitextMining</h1>
  <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>
  <div style="font-size: 0.9rem; color: #2c5282; margin-top: 10px;">Massive Text Embedding Benchmark</div>
</div>

The IWSLT 2017 Multilingual Task addresses text translation, including zero-shot translation, with a single MT system across all directions including English, German, Dutch, Italian and Romanian.

|               |                                             |
|---------------|---------------------------------------------|
| Task category | t2t                              |
| Domains       | Non-fiction, Fiction, Written                               |
| Reference     | https://aclanthology.org/2017.iwslt-1.1/ |


## 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(["IWSLT2017BitextMining"])
evaluator = mteb.MTEB(task)

model = mteb.get_model(YOUR_MODEL)
evaluator.run(model)
```

<!-- Datasets want link to arxiv in readme to autolink dataset with paper -->
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{cettolo-etal-2017-overview,
  address = {Tokyo, Japan},
  author = {Cettolo, Mauro  and
Federico, Marcello  and
Bentivogli, Luisa  and
Niehues, Jan  and
St{\"u}ker, Sebastian  and
Sudoh, Katsuhito  and
Yoshino, Koichiro  and
Federmann, Christian},
  booktitle = {Proceedings of the 14th International Conference on Spoken Language Translation},
  editor = {Sakti, Sakriani  and
Utiyama, Masao},
  month = dec # { 14-15},
  pages = {2--14},
  publisher = {International Workshop on Spoken Language Translation},
  title = {Overview of the {IWSLT} 2017 Evaluation Campaign},
  url = {https://aclanthology.org/2017.iwslt-1.1},
  year = {2017},
}


@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
<details>
  <summary> Dataset Statistics</summary>

The following code contains the descriptive statistics from the task. These can also be obtained using:

```python
import mteb

task = mteb.get_task("IWSLT2017BitextMining")

desc_stats = task.metadata.descriptive_stats
```

```json
{
    "validation": {
        "num_samples": 21938,
        "number_of_characters": 4256244,
        "unique_pairs": 21840,
        "min_sentence1_length": 2,
        "average_sentence1_length": 97.0061992889051,
        "max_sentence1_length": 521,
        "unique_sentence1": 11563,
        "min_sentence2_length": 2,
        "average_sentence2_length": 97.0061992889051,
        "max_sentence2_length": 521,
        "unique_sentence2": 11563
    }
}
```

</details>

---
*This dataset card was automatically generated using [MTEB](https://github.com/embeddings-benchmark/mteb)*