2A2I/Arabic_Aya

Dataset Card for : Arabic Aya (2A)

Arabic Aya (2A) : A Curated Subset of the Aya Collection for Arabic Language Processing

Dataset Sources & Infos

• Data Origin: Derived from 69 subsets of the original Aya datasets : CohereForAI/aya_collection, CohereForAI/aya_dataset, and CohereForAI/aya_evaluation_suite.
• Languages: Modern Standard Arabic (MSA) and a variety of Arabic dialects ( 'arb', 'arz', 'ary', 'ars', 'knc', 'acm', 'apc', 'aeb', 'ajp', 'acq' )
• Applications: Language Modeling, Text Classification, Sentiment Analysis, Dialect Identification, Translation
• Paper: 2402.06619
• Maintainer: Elfilali Ali
• License: Apache-2.0

Overview

Arabic Aya is a meticulously curated dataset derived from the comprehensive Aya collection by CohereForAI, specifically focusing on Arabic text data. This dataset aggregates content from the CohereForAI/aya_collection, CohereForAI/aya_dataset, and CohereForAI/aya_evaluation_suite, filtering out all but the Arabic content, including both Modern Standard Arabic (MSA) and various regional dialects.

Purpose

The aim of 'Arabic Aya' is to provide researchers, technologists, and linguists with a ready-to-use Arabic text resource, significantly reducing the time and effort required for data preprocessing in NLP and AI projects focused on the Arabic language.

• Use the Aya datasets out of the box for your Arabic applications and research 😀

Usage

This dataset serves as a foundational tool for those embarking on Arabic language projects, from academic research to commercial applications. By providing a pre-filtered source of Arabic text, 'Arabic Aya' enables users to dive straight into model training, analysis, and application development without the preliminary hassle of data cleaning and language filtering.

Use with HuggingFace's datasets library

To load this dataset with Datasets, you'll need to install Datasets as pip install datasets --upgrade and then use a similar code to the following:

from datasets import load_dataset

dataset = load_dataset("2A2I/Arabic_Aya", "CohereForAI-aya_collection-templated_mintaka")

In the above code snippet, "CohereForAI-aya_collection-templated_mintaka" refers to the arabic version (100k rows) of the original "templated_mintaka" subset (780k rows) of the aya_collection. You can load other subsets by specifying its name at the time of loading the dataset.

Access and Contribution

Available on the Hugging Face Hub under 2A2I/Arabic_Aya, 'Arabic Aya' invites contributions from the community. Users are encouraged to offer feedback, suggest improvements.

Support and Collaboration

We are committed to fostering an inclusive and supportive environment around Arabic AI and NLP research. For support, collaboration, or queries regarding the dataset, please reach out through the Hugging Face Hub's discussion section or reach out at 2A2I Contact Email.

Original Dataset Card of Aya by CohereForAI

Dataset Summary

The Aya Collection is a massive multilingual collection consisting of 513 million instances of prompts and completions covering a wide range of tasks. This collection incorporates instruction-style templates from fluent speakers and applies them to a curated list of datasets, as well as translations of instruction-style datasets into 101 languages. Aya Dataset, a human-curated multilingual instruction and response dataset, is also part of this collection. See our paper for more details regarding the collection.

• Curated by: Contributors of Aya Open Science Intiative

• Language(s): 115 languages

• License: Apache 2.0

• Aya Datasets Family:

  Name	Explanation
  aya_dataset	Human-annotated multilingual instruction finetuning dataset, comprising over 204K instances across 65 languages.
  aya_collection	Created by applying instruction-style templates from fluent speakers to 44 datasets, including translations of 19 instruction-style datasets into 101 languages.
  aya_evaluation_suite	A diverse evaluation set for multilingual open-ended generation, featuring 250 culturally grounded prompts in 7 languages, 200 translated prompts in 24 languages, and human-edited versions selected for cross-cultural relevance from English Dolly in 6 languages.

Dataset

The Aya Collection is a comprehensive, large corpus of datasets that can be used by researchers around the world to train multilingual models. Our goal is only to include datasets with permissive licensing for manipulation and redistribution.

The Aya Collection consists of three different sources of data:

1. Templated data: We collaborated with fluent speakers to create templates that allowed for the automatic expansion of existing datasets into various languages.
2. Translated data: We translated a hand-selected subset of 19 datasets into 101 languages (114 dialects) using the NLLB 3.3B parameter machine translation model.
3. Aya Dataset: We release the Aya Dataset as a subset of the overall collection. This is the only dataset in the collection that is human-annotated in its entirety.

Load with Datasets

To load this dataset with Datasets, you'll need to install Datasets as pip install datasets --upgrade and then use the following code:

from datasets import load_dataset

dataset = load_dataset("CohereForAI/aya_collection", "templated_mintaka")

In the above code snippet, "templated_mintaka" refers to a subset of the aya_collection. You can load other subsets by specifying its name at the time of loading the dataset.

Data Instances

An example of a train instance looks as follows:

{'id': 246001,
 'inputs': 'The following query in English is taken from the geography category. What could be the answer to the question?\nWhat is the seventh tallest mountain in North America?',
 'targets': 'The answer is Mount Lucania.',
 'dataset_name': 'Mintaka-inst',
 'sub_dataset_name': '-',
 'task_type': 'question-answering',
 'template_id': 3,
 'language': 'eng',
 'split': 'train',
 'script': 'Latn'
}

Data Fields

The data fields are the same among all splits:

• id: Unique id of the data point
• inputs: Prompt or input to the language model.
• targets: Completion or output of the language model.
• dataset_name: The name of the source dataset that the data point was taken from
• sub_dataset_name: If the source is a collection, this field indicates which part of that collection the data point was taken from. If it is not a collection, this field is left blank.
• task_type: The task type that this conversation belongs to.
• template_id: The id of the template applied to this data point.
• language: The ISO code of the dialect of the conversation.
• script: The script of the language.
• split: Indicates whether the data point is part of the train or the test split.

Statistics

The total number of data points, including the Aya Dataset` is 513,758,189. To view the breakdown of dialect codes and the respective templated and translated data point counts in the Aya Collection , refer to the toggled table below.

Breakdown of Aya Collection data point counts grouped by dialects

dialect code	language	translated data point count	templated data point count	total count
ace	Achinese	8240684	2000	8242684
acm	Arabic	4120342	0	4120342
acq	Arabic	4120342	0	4120342
aeb	Arabic	4120342	0	4120342
afr	Afrikaans	4120342	6108	4126450
ajp	Arabic	4120342	0	4120342
als	Albanian	4120342	0	4120342
amh	Amharic	4120342	25327	4145669
apc	Arabic	4120342	0	4120342
arb	Arabic	6424999	216430	6641429
ars	Arabic	4120342	0	4120342
ary	Arabic	4120342	18076	4138418
arz	Arabic	4120342	0	4120342
azb	Azerbaijani	4120342	0	4120342
azj	Azerbaijani	4120342	0	4120342
bel	Belarusian	4120342	21273	4141615
ben	Bengali	4120342	30661	4151003
bjn	Banjar	8240684	2000	8242684
bul	Bulgarian	4120342	37722	4158064
cat	Catalan	4120342	66900	4187242
ceb	Cebuano	4120342	0	4120342
ces	Czech	4120342	179604	4299946
ckb	Kurdish	4120342	0	4120342
cym	Welsh	4120342	0	4120342
dan	Danish	4120342	36310	4156652
deu	German	4120342	1326722	5447064
ell	Greek	4120342	40291	4160633
eng	English	9771427	8066678	17838105
epo	Esperanto	4120342	0	4120342
est	Estonian	4120342	0	4120342
eus	Basque	4120342	0	4120342
fin	Finnish	4120342	457895	4578237
fra	French	4120342	835520	4955862
gla	Scottish Gaelic	4120342	0	4120342
gle	Irish	4120342	0	4120342
glg	Galician	4120342	0	4120342
guj	Gujarati	4120342	2157	4122499
hat	Haitian Creole	4120342	0	4120342
hau	Hausa	4120342	51396	4171738
heb	Hebrew	4120342	103466	4223808
hin	Hindi	4120342	260387	4380729
hun	Hungarian	4120342	82039	4202381
hye	Armenian	4120342	7080	4127422
ibo	Igbo	4120342	36312	4156654
ind	Indonesian	4120342	45709	4166051
isl	Icelandic	4120342	0	4120342
ita	Italian	4120342	405682	4526024
jav	Javanese	4120342	829	4121171
jpn	Japanese	4120342	2693177	6813519
kan	Kannada	4120342	1156	4121498
kas	Kashmiri	4120342	0	4120342
kat	Georgian	4120342	0	4120342
kaz	Kazakh	4120342	0	4120342
khk	Mongolian	4120342	0	4120342
khm	Khmer	4120342	0	4120342
kir	Kyrgyz	4120342	0	4120342
kmr	Kurdish	4120342	0	4120342
knc	Kanuri	8240684	0	8240684
kor	Korean	4120342	41011	4161353
lao	Lao	4120342	0	4120342
lit	Lithuanian	4120342	0	4120342
ltz	Luxembourgish	4120342	0	4120342
lvs	Latvian	4120342	0	4120342
mal	Malayalam	4120342	4347	4124689
mar	Marathi	4120342	3678	4124020
min	Minangkabau	6753788	2000	6755788
mkd	Macedonian	4120342	0	4120342
mlt	Maltese	4120342	0	4120342
mni	Manipuri	4120342	0	4120342
mri	Maori	4120342	0	4120342
mya	Burmese	4120342	0	4120342
nld	Dutch	4120342	220181	4340523
nno	Norwegian	4120342	0	4120342
nob	Norwegian	4120342	0	4120342
npi	Nepali	4120342	0	4120342
nso	Northern Sotho	4120342	0	4120342
pbt	Pashto	4120342	0	4120342
pes	Persian	4120342	245520	4365862
plt	Malagasy	4120342	0	4120342
pol	Polish	4120342	332503	4452845
por	Portuguese	4120342	287432	4407774
ron	Romanian	4120342	36359	4156701
rus	Russian	4120342	545920	4666262
sin	Sinhala	4120342	195	4120537
slk	Slovak	4120342	27845	4148187
slv	Slovenian	4120342	25731	4146073
smo	Samoan	4120342	0	4120342
sna	Shona	4120342	3684	4124026
snd	Sindhi	4120342	0	4120342
som	Somali	4120342	2926	4123268
sot	Southern Sotho	4120342	0	4120342
spa	Spanish	4120342	379194	4499536
srp	Serbian	4120342	77124	4197466
sun	Sundanese	4120342	2208	4122550
swe	Swedish	4120342	76486	4196828
swh	Swahili	4120342	12726	4133068
tam	Tamil	4120342	11462	4131804
taq	Tamasheq	4120342	0	4120342
tel	Telugu	4120342	477821	4598163
tgk	Tajik	4120342	0	4120342
tha	Thai	4120342	2125180	6245522
tur	Turkish	4120342	59932	4180274
ukr	Ukrainian	4120342	189384	4309726
urd	Urdu	4120342	337739	4458081
uzn	Uzbek	4120342	0	4120342
vie	Vietnamese	4120342	42232	4162574
xho	Xhosa	4120342	2952	4123294
ydd	Yiddish	4120342	0	4120342
yor	Yoruba	4120342	4907	4125249
yue	Chinese	4120342	0	4120342
zho-Hans	Chinese	4120342	54528	4174870
zho-Hant	Chinese	4120342	0	4120342
zsm	Malay	4120342	13950	4134292
zul	Zulu	4120342	786	4121128
arq	Arabic	0	6046	6046
ban	Balinese	0	2000	2000
bbc	Toba Batak	0	2000	2000
bem	Bemba	0	776	776
fil	Filipino	0	220	220
fon	Fon	0	845	845
hrv	Croatian	0	9007	9007
kin	Kinyarwanda	0	11165	11165
lij	Ligurian	0	6409	6409
mad	Madurese	0	2000	2000
nij	Ngaju	0	2000	2000
nor	Norwegian	0	72352	72352
pan	Punjabi	0	2156	2156
twi	Twi	0	10840	10840
wol	Wolof	0	785	785
zho	Chinese	0	74972	74972

PS: Templated data also includes Mozambican Portuguese, which doesn't have its own ISO language code.

Motivations & Intentions

• Curation Rationale: Automatic augmentation of existing datasets serves to enhance the available linguistic resources for multiple languages. The list of languages was initially established from mT5 and aligned with the annotators’ language list and NLLB translation model. The datasets were translated directly from English for all languages.

Additional Information

Provenance

• Methods Used: A combination of crowd-sourced templating and automatic translation was employed to source this dataset.
• Methodology Details:
  • Source: Existing NLP datasets
  • Dates of Collection: May 2023 - Dec 2023

Dataset Version and Maintenance

• Maintenance Status: Actively Maintained
• Version Details:
  • Current version: 1.0
  • Last Update: 02/2024
  • First Release: 02/2024

Authorship

• Publishing Organization: Cohere For AI
• Industry Type: Not-for-profit - Tech
• Contact Details: https://cohere.com/research/aya

Licensing Information

This dataset can be used for any purpose, whether academic or commercial, under the terms of the Apache 2.0 License.

Citation Information

@misc{singh2024aya,
      title={Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning}, 
      author={Shivalika Singh and Freddie Vargus and Daniel Dsouza and Börje F. Karlsson and Abinaya Mahendiran and Wei-Yin Ko and Herumb Shandilya and Jay Patel and Deividas Mataciunas and Laura OMahony and Mike Zhang and Ramith Hettiarachchi and Joseph Wilson and Marina Machado and Luisa Souza Moura and Dominik Krzemiński and Hakimeh Fadaei and Irem Ergün and Ifeoma Okoh and Aisha Alaagib and Oshan Mudannayake and Zaid Alyafeai and Vu Minh Chien and Sebastian Ruder and Surya Guthikonda and Emad A. Alghamdi and Sebastian Gehrmann and Niklas Muennighoff and Max Bartolo and Julia Kreutzer and Ahmet Üstün and Marzieh Fadaee and Sara Hooker},
      year={2024},
      eprint={2402.06619},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}