MMTEB: Massive Multilingual Text Embedding Benchmark
Paper • 2502.13595 • Published • 50
Datasets:
id string | text string |
|---|---|
0 | a close up photo of a 'red and white circle 20 kph speed limit
' traffic sign. |
1 | a close up photo of a 'red and white circle 30 kph speed limit
' traffic sign. |
2 | a close up photo of a 'red and white circle 50 kph speed limit
' traffic sign. |
3 | a close up photo of a 'red and white circle 60 kph speed limit
' traffic sign. |
4 | a close up photo of a 'red and white circle 70 kph speed limit
' traffic sign. |
5 | a close up photo of a 'red and white circle 80 kph speed limit
' traffic sign. |
6 | a close up photo of a 'end / de-restriction of 80 kph speed limit
' traffic sign. |
7 | a close up photo of a 'red and white circle 100 kph speed limit
' traffic sign. |
8 | a close up photo of a 'red and white circle 120 kph speed limit
' traffic sign. |
9 | a close up photo of a 'red and white circle red car and black car no passing
' traffic sign. |
10 | a close up photo of a 'red and white circle red truck and black car no passing
' traffic sign. |
11 | a close up photo of a 'red and white triangle road intersection warning
' traffic sign. |
12 | a close up photo of a 'white and yellow diamond priority road
' traffic sign. |
13 | a close up photo of a 'red and white upside down triangle yield right-of-way
' traffic sign. |
14 | a close up photo of a 'stop
' traffic sign. |
15 | a close up photo of a 'empty red and white circle
' traffic sign. |
16 | a close up photo of a 'red and white circle no truck entry
' traffic sign. |
17 | a close up photo of a 'red circle with white horizonal stripe no entry
' traffic sign. |
18 | a close up photo of a 'red and white triangle with exclamation mark warning
' traffic sign. |
19 | a close up photo of a 'red and white triangle with black left curve approaching warning
' traffic sign. |
20 | a close up photo of a 'red and white triangle with black right curve approaching warning
' traffic sign. |
21 | a close up photo of a 'red and white triangle with black double curve approaching warning
' traffic sign. |
22 | a close up photo of a 'red and white triangle rough / bumpy road warning
' traffic sign. |
23 | a close up photo of a 'red and white triangle car skidding / slipping warning
' traffic sign. |
24 | a close up photo of a 'red and white triangle with merging / narrow lanes warning
' traffic sign. |
25 | a close up photo of a 'red and white triangle with person digging / construction / road work warning
' traffic sign. |
26 | a close up photo of a 'red and white triangle with traffic light approaching warning
' traffic sign. |
27 | a close up photo of a 'red and white triangle with person walking warning
' traffic sign. |
28 | a close up photo of a 'red and white triangle with child and person walking warning
' traffic sign. |
29 | a close up photo of a 'red and white triangle with bicyle warning
' traffic sign. |
30 | a close up photo of a 'red and white triangle with snowflake / ice warning
' traffic sign. |
31 | a close up photo of a 'red and white triangle with deer warning
' traffic sign. |
32 | a close up photo of a 'white circle with gray strike bar no speed limit
' traffic sign. |
33 | a close up photo of a 'blue circle with white right turn arrow mandatory
' traffic sign. |
34 | a close up photo of a 'blue circle with white left turn arrow mandatory
' traffic sign. |
35 | a close up photo of a 'blue circle with white forward arrow mandatory
' traffic sign. |
36 | a close up photo of a 'blue circle with white forward or right turn arrow mandatory
' traffic sign. |
37 | a close up photo of a 'blue circle with white forward or left turn arrow mandatory
' traffic sign. |
38 | a close up photo of a 'blue circle with white keep right arrow mandatory
' traffic sign. |
39 | a close up photo of a 'blue circle with white keep left arrow mandatory
' traffic sign. |
40 | a close up photo of a 'blue circle with white arrows indicating a traffic circle
' traffic sign. |
41 | a close up photo of a 'white circle with gray strike bar indicating no passing for cars has ended
' traffic sign. |
42 | a close up photo of a 'white circle with gray strike bar indicating no passing for trucks has ended
' traffic sign. |
The German Traffic Sign Recognition Benchmark (GTSRB) is a multi-class classification dataset for traffic signs. It consists of dataset of more than 50,000 traffic sign images. The dataset comprises 43 classes with unbalanced class frequencies.
| Task category | ZeroShotClassification (image-to-text) |
| Domains | Scene |
| Reference | The 2011 International Joint Conference on Neural Networks |
Source datasets:
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_task("GTSRBZeroShot")
model = mteb.get_model(YOUR_MODEL)
mteb.evaluate(model, task)
To learn more about how to run models on mteb task check out the GitHub repository.
Citation
If you use this dataset, please cite the dataset as well as mteb, as this dataset likely includes additional processing as a part of the MMTEB Contribution.
@inproceedings{6033395,
author = {Stallkamp, Johannes and Schlipsing, Marc and Salmen, Jan and Igel, Christian},
booktitle = {The 2011 International Joint Conference on Neural Networks},
doi = {10.1109/IJCNN.2011.6033395},
keywords = {Humans;Training;Image color analysis;Benchmark testing;Lead;Histograms;Image resolution},
number = {},
pages = {1453-1460},
title = {The German Traffic Sign Recognition Benchmark: A multi-class classification competition},
volume = {},
year = {2011},
}
@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, Loïc 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:
import mteb
task = mteb.get_task("GTSRBZeroShot")
desc_stats = task.metadata.descriptive_stats
{
"test": {
"num_samples": 12630,
"number_of_characters": null,
"text_statistics": null,
"image_statistics": {
"min_image_width": 25,
"average_image_width": 50.50775930324624,
"max_image_width": 266,
"min_image_height": 25,
"average_image_height": 50.36444972288203,
"max_image_height": 232,
"unique_images": 12630
},
"label_statistics": {
"min_labels_per_text": 1,
"average_label_per_text": 1.0,
"max_labels_per_text": 1,
"unique_labels": 43,
"labels": {
"16": {
"count": 150
},
"1": {
"count": 720
},
"38": {
"count": 690
},
"33": {
"count": 210
},
"11": {
"count": 420
},
"18": {
"count": 390
},
"12": {
"count": 690
},
"25": {
"count": 480
},
"35": {
"count": 390
},
"7": {
"count": 450
},
"23": {
"count": 150
},
"4": {
"count": 660
},
"9": {
"count": 480
},
"21": {
"count": 90
},
"20": {
"count": 90
},
"27": {
"count": 60
},
"3": {
"count": 450
},
"13": {
"count": 720
},
"10": {
"count": 660
},
"5": {
"count": 630
},
"17": {
"count": 360
},
"34": {
"count": 120
},
"2": {
"count": 750
},
"8": {
"count": 450
},
"30": {
"count": 150
},
"24": {
"count": 90
},
"15": {
"count": 210
},
"26": {
"count": 180
},
"28": {
"count": 150
},
"22": {
"count": 120
},
"14": {
"count": 270
},
"32": {
"count": 60
},
"29": {
"count": 90
},
"6": {
"count": 150
},
"36": {
"count": 120
},
"40": {
"count": 90
},
"41": {
"count": 60
},
"31": {
"count": 270
},
"19": {
"count": 60
},
"0": {
"count": 60
},
"39": {
"count": 90
},
"42": {
"count": 90
},
"37": {
"count": 60
}
}
},
"candidates_labels_text_statistics": {
"total_text_length": 3795,
"min_text_length": 43,
"average_text_length": 88.25581395348837,
"max_text_length": 116,
"unique_texts": 43
}
}
}
This dataset card was automatically generated using MTEB
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