Datasets:
metadata
annotations_creators:
- derived
language:
- amh
- eng
- fra
- hau
- ibo
- lin
- lug
- orm
- pcm
- run
- sna
- som
- swa
- tir
- xho
- yor
license: afl-3.0
multilinguality: multilingual
task_categories:
- text-classification
task_ids: []
dataset_info:
- config_name: amh
features:
- name: sentences
sequence: string
- name: labels
sequence: int64
splits:
- name: test
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- name: labels
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- name: labels
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- name: labels
sequence: int64
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- config_name: ibo
features:
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sequence: string
- name: labels
sequence: int64
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- name: test
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- config_name: lin
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- name: labels
sequence: int64
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- config_name: lug
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- name: sentences
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- name: labels
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- config_name: orm
features:
- name: sentences
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- name: labels
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splits:
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- config_name: pcm
features:
- name: sentences
sequence: string
- name: labels
sequence: int64
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- config_name: run
features:
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- name: labels
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- config_name: sna
features:
- name: sentences
sequence: string
- name: labels
sequence: int64
splits:
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- config_name: som
features:
- name: sentences
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- name: labels
sequence: int64
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- config_name: swa
features:
- name: sentences
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sequence: int64
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- config_name: tir
features:
- name: sentences
sequence: string
- name: labels
sequence: int64
splits:
- name: test
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dataset_size: 1482817
- config_name: xho
features:
- name: sentences
sequence: string
- name: labels
sequence: int64
splits:
- name: test
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download_size: 365340
dataset_size: 584125
- config_name: yor
features:
- name: sentences
sequence: string
- name: labels
sequence: int64
splits:
- name: test
num_bytes: 1051099
num_examples: 5
download_size: 570345
dataset_size: 1051099
configs:
- config_name: amh
data_files:
- split: test
path: amh/test-*
- config_name: eng
data_files:
- split: test
path: eng/test-*
- config_name: fra
data_files:
- split: test
path: fra/test-*
- config_name: hau
data_files:
- split: test
path: hau/test-*
- config_name: ibo
data_files:
- split: test
path: ibo/test-*
- config_name: lin
data_files:
- split: test
path: lin/test-*
- config_name: lug
data_files:
- split: test
path: lug/test-*
- config_name: orm
data_files:
- split: test
path: orm/test-*
- config_name: pcm
data_files:
- split: test
path: pcm/test-*
- config_name: run
data_files:
- split: test
path: run/test-*
- config_name: sna
data_files:
- split: test
path: sna/test-*
- config_name: som
data_files:
- split: test
path: som/test-*
- config_name: swa
data_files:
- split: test
path: swa/test-*
- config_name: tir
data_files:
- split: test
path: tir/test-*
- config_name: xho
data_files:
- split: test
path: xho/test-*
- config_name: yor
data_files:
- split: test
path: yor/test-*
tags:
- mteb
- text
Clustering of news article headlines and texts from MasakhaNEWS dataset. Clustering of 10 sets on the news article label.
| Task category | t2c |
| Domains | News, Written, Non-fiction |
| Reference | https://huggingface.co/datasets/masakhane/masakhanews |
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["MasakhaNEWSClusteringP2P"])
evaluator = mteb.MTEB(task)
model = mteb.get_model(YOUR_MODEL)
evaluator.run(model)
To learn more about how to run models on mteb task check out the GitHub repitory.
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.
@article{adelani2023masakhanews,
author = {David Ifeoluwa Adelani and Marek Masiak and Israel Abebe Azime and Jesujoba Oluwadara Alabi and Atnafu Lambebo Tonja and Christine Mwase and Odunayo Ogundepo and Bonaventure F. P. Dossou and Akintunde Oladipo and Doreen Nixdorf and Chris Chinenye Emezue and Sana Sabah al-azzawi and Blessing K. Sibanda and Davis David and Lolwethu Ndolela and Jonathan Mukiibi and Tunde Oluwaseyi Ajayi and Tatiana Moteu Ngoli and Brian Odhiambo and Abraham Toluwase Owodunni and Nnaemeka C. Obiefuna and Shamsuddeen Hassan Muhammad and Saheed Salahudeen Abdullahi and Mesay Gemeda Yigezu and Tajuddeen Gwadabe and Idris Abdulmumin and Mahlet Taye Bame and Oluwabusayo Olufunke Awoyomi and Iyanuoluwa Shode and Tolulope Anu Adelani and Habiba Abdulganiy Kailani and Abdul-Hakeem Omotayo and Adetola Adeeko and Afolabi Abeeb and Anuoluwapo Aremu and Olanrewaju Samuel and Clemencia Siro and Wangari Kimotho and Onyekachi Raphael Ogbu and Chinedu E. Mbonu and Chiamaka I. Chukwuneke and Samuel Fanijo and Jessica Ojo and Oyinkansola F. Awosan and Tadesse Kebede Guge and Sakayo Toadoum Sari and Pamela Nyatsine and Freedmore Sidume and Oreen Yousuf and Mardiyyah Oduwole and Ussen Kimanuka and Kanda Patrick Tshinu and Thina Diko and Siyanda Nxakama and Abdulmejid Tuni Johar and Sinodos Gebre and Muhidin Mohamed and Shafie Abdi Mohamed and Fuad Mire Hassan and Moges Ahmed Mehamed and Evrard Ngabire and and Pontus Stenetorp},
journal = {ArXiv},
title = {MasakhaNEWS: News Topic Classification for African languages},
volume = {},
year = {2023},
}
@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
Dataset Statistics
The following code contains the descriptive statistics from the task. These can also be obtained using:
import mteb
task = mteb.get_task("MasakhaNEWSClusteringP2P")
desc_stats = task.metadata.descriptive_stats
{
"test": {
"num_samples": 80,
"number_of_characters": 6242,
"min_text_length": 35,
"average_text_length": 78.025,
"max_text_length": 190,
"unique_texts": 6236,
"min_labels_per_text": 286,
"average_labels_per_text": 78.025,
"max_labels_per_text": 1589,
"unique_labels": 7,
"labels": {
"0": {
"count": 785
},
"2": {
"count": 1258
},
"3": {
"count": 1589
},
"5": {
"count": 1265
},
"1": {
"count": 762
},
"6": {
"count": 297
},
"4": {
"count": 286
}
}
}
}
This dataset card was automatically generated using MTEB