MMTEB: Massive Multilingual Text Embedding Benchmark
Paper • 2502.13595 • Published • 50
Datasets:
id stringlengths 1 3 | text stringlengths 31 51 |
|---|---|
0 | a photo of apple_pie, a type of food. |
1 | a photo of baby_back_ribs, a type of food. |
2 | a photo of baklava, a type of food. |
3 | a photo of beef_carpaccio, a type of food. |
4 | a photo of beef_tartare, a type of food. |
5 | a photo of beet_salad, a type of food. |
6 | a photo of beignets, a type of food. |
7 | a photo of bibimbap, a type of food. |
8 | a photo of bread_pudding, a type of food. |
9 | a photo of breakfast_burrito, a type of food. |
10 | a photo of bruschetta, a type of food. |
11 | a photo of caesar_salad, a type of food. |
12 | a photo of cannoli, a type of food. |
13 | a photo of caprese_salad, a type of food. |
14 | a photo of carrot_cake, a type of food. |
15 | a photo of ceviche, a type of food. |
16 | a photo of cheesecake, a type of food. |
17 | a photo of cheese_plate, a type of food. |
18 | a photo of chicken_curry, a type of food. |
19 | a photo of chicken_quesadilla, a type of food. |
20 | a photo of chicken_wings, a type of food. |
21 | a photo of chocolate_cake, a type of food. |
22 | a photo of chocolate_mousse, a type of food. |
23 | a photo of churros, a type of food. |
24 | a photo of clam_chowder, a type of food. |
25 | a photo of club_sandwich, a type of food. |
26 | a photo of crab_cakes, a type of food. |
27 | a photo of creme_brulee, a type of food. |
28 | a photo of croque_madame, a type of food. |
29 | a photo of cup_cakes, a type of food. |
30 | a photo of deviled_eggs, a type of food. |
31 | a photo of donuts, a type of food. |
32 | a photo of dumplings, a type of food. |
33 | a photo of edamame, a type of food. |
34 | a photo of eggs_benedict, a type of food. |
35 | a photo of escargots, a type of food. |
36 | a photo of falafel, a type of food. |
37 | a photo of filet_mignon, a type of food. |
38 | a photo of fish_and_chips, a type of food. |
39 | a photo of foie_gras, a type of food. |
40 | a photo of french_fries, a type of food. |
41 | a photo of french_onion_soup, a type of food. |
42 | a photo of french_toast, a type of food. |
43 | a photo of fried_calamari, a type of food. |
44 | a photo of fried_rice, a type of food. |
45 | a photo of frozen_yogurt, a type of food. |
46 | a photo of garlic_bread, a type of food. |
47 | a photo of gnocchi, a type of food. |
48 | a photo of greek_salad, a type of food. |
49 | a photo of grilled_cheese_sandwich, a type of food. |
50 | a photo of grilled_salmon, a type of food. |
51 | a photo of guacamole, a type of food. |
52 | a photo of gyoza, a type of food. |
53 | a photo of hamburger, a type of food. |
54 | a photo of hot_and_sour_soup, a type of food. |
55 | a photo of hot_dog, a type of food. |
56 | a photo of huevos_rancheros, a type of food. |
57 | a photo of hummus, a type of food. |
58 | a photo of ice_cream, a type of food. |
59 | a photo of lasagna, a type of food. |
60 | a photo of lobster_bisque, a type of food. |
61 | a photo of lobster_roll_sandwich, a type of food. |
62 | a photo of macaroni_and_cheese, a type of food. |
63 | a photo of macarons, a type of food. |
64 | a photo of miso_soup, a type of food. |
65 | a photo of mussels, a type of food. |
66 | a photo of nachos, a type of food. |
67 | a photo of omelette, a type of food. |
68 | a photo of onion_rings, a type of food. |
69 | a photo of oysters, a type of food. |
70 | a photo of pad_thai, a type of food. |
71 | a photo of paella, a type of food. |
72 | a photo of pancakes, a type of food. |
73 | a photo of panna_cotta, a type of food. |
74 | a photo of peking_duck, a type of food. |
75 | a photo of pho, a type of food. |
76 | a photo of pizza, a type of food. |
77 | a photo of pork_chop, a type of food. |
78 | a photo of poutine, a type of food. |
79 | a photo of prime_rib, a type of food. |
80 | a photo of pulled_pork_sandwich, a type of food. |
81 | a photo of ramen, a type of food. |
82 | a photo of ravioli, a type of food. |
83 | a photo of red_velvet_cake, a type of food. |
84 | a photo of risotto, a type of food. |
85 | a photo of samosa, a type of food. |
86 | a photo of sashimi, a type of food. |
87 | a photo of scallops, a type of food. |
88 | a photo of seaweed_salad, a type of food. |
89 | a photo of shrimp_and_grits, a type of food. |
90 | a photo of spaghetti_bolognese, a type of food. |
91 | a photo of spaghetti_carbonara, a type of food. |
92 | a photo of spring_rolls, a type of food. |
93 | a photo of steak, a type of food. |
94 | a photo of strawberry_shortcake, a type of food. |
95 | a photo of sushi, a type of food. |
96 | a photo of tacos, a type of food. |
97 | a photo of takoyaki, a type of food. |
98 | a photo of tiramisu, a type of food. |
99 | a photo of tuna_tartare, a type of food. |
End of preview. Expand in Data Studio
Classifying food.
| Task category | ZeroShotClassification (image-to-text) |
| Domains | Web |
| Reference | European Conference on Computer Vision |
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("Food101ZeroShot")
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{bossard14,
author = {Bossard, Lukas and Guillaumin, Matthieu and Van Gool, Luc},
booktitle = {European Conference on Computer Vision},
title = {Food-101 -- Mining Discriminative Components with Random Forests},
year = {2014},
}
@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("Food101ZeroShot")
desc_stats = task.metadata.descriptive_stats
{
"validation": {
"num_samples": 25250,
"number_of_characters": null,
"text_statistics": null,
"image_statistics": {
"min_image_width": 287,
"average_image_width": 495.818495049505,
"max_image_width": 512,
"min_image_height": 213,
"average_image_height": 475.08229702970294,
"max_image_height": 512,
"unique_images": 25246
},
"label_statistics": {
"min_labels_per_text": 1,
"average_label_per_text": 1.0,
"max_labels_per_text": 1,
"unique_labels": 101,
"labels": {
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},
"candidates_labels_text_statistics": {
"total_text_length": 3911,
"min_text_length": 31,
"average_text_length": 38.722772277227726,
"max_text_length": 51,
"unique_texts": 101
}
}
}
This dataset card was automatically generated using MTEB
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