AfroXLMR-large-76L was created by an MLM adaptation of the expanded XLM-R-large model on 76 languages widely spoken in Africa
including 4 high-resource languages.
Pre-training corpus
A mix of mC4, Wikipedia and OPUS data
Languages
There are 76 languages available :
English (eng)
Amharic (amh)
Arabic (ara)
Somali (som)
Kiswahili (swa)
Portuguese (por)
Afrikaans (afr)
French (fra)
isiZulu (zul)
Malagasy (mlg)
Hausa (hau)
chiShona (sna)
Egyptian Arabic (arz)
Chichewa (nya)
Igbo (ibo)
isiXhosa (xho)
Yorùbá (yor)
Sesotho (sot)
Kinyarwanda (kin)
Tigrinya (tir)
Tsonga (tso)
Oromo (orm)
Rundi (run)
Northern Sotho (nso)
Ewe (ewe)
Lingala (lin)
Twi (twi)
Nigerian Pidgin (pcm)
Ga (gaa)
Lozi (loz)
Luganda (lug)
Gun (guw)
Bemba (bem)
Efik (efi)
Luvale (lue)
Luba-Lulua (lua)
Tonga (toi)
Tshivenḓa (ven)
Tumbuka (tum)
Tetela (tll)
Isoko (iso)
Kaonde (kqn)
Zande (zne)
Umbundu (umb)
Mossi (mos)
Tiv (tiv)
Luba-Katanga (lub)
Fula (fuv)
San Salvador Kongo (kwy)
Baoulé (bci)
Ruund (rnd)
Luo (luo)
Wolaitta (wal)
Swazi (ssw)
Lunda (lun)
Wolof (wol)
Nyaneka (nyk)
Kwanyama (kua)
Kikuyu (kik)
Fon (fon)
Bambara (bam)
Chokwe (cjk)
Dinka (dik)
Dyula (dyu)
Kabyle (kab)
Kamba (kam)
Kabiyè (kbp)
Kanuri (knc)
Kimbundu (kmb)
Kikongo (kon)
Nuer (nus)
Sango (sag)
Tamasheq (taq)
Tamazight (tzm)
N'ko (nqo)
Acknowledgment
We would like to thank Google Cloud for providing us access to TPU v3-8 through the free cloud credits. Model trained using flax, before converted to pytorch.
BibTeX entry and citation info.
@misc{adelani2023sib200,
title={SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects},
author={David Ifeoluwa Adelani and Hannah Liu and Xiaoyu Shen and Nikita Vassilyev and Jesujoba O. Alabi and Yanke Mao and Haonan Gao and Annie En-Shiun Lee},
year={2023},
eprint={2309.07445},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Runs of Davlan afro-xlmr-large-76L on huggingface.co
926
Total runs
-18
24-hour runs
-24
3-day runs
40
7-day runs
322
30-day runs
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