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CulturaY: A Large Cleaned Multilingual Dataset of 75 Languages

Dataset Summary

From the team that brought you CulturaX, we present CulturaY, another substantial multilingual dataset of 15TB (uncompressed)/3TB (zstd-compressed) that applies the same dataset cleaning methodology to the HPLT v1.1 dataset. Please note that HPLT v1.2 has also been released and is an alternative verison with different cleaning methodolgies. This data was used in part to train our SOTA Vietnamese model: Vistral-7B-Chat.

Our annotations and arrangements are licensed under CC-BY-4.0, and we make the data available for fair use machine learning research.
But we make no claims as to the underlying copyrights of the work. This data was copied from the HPLT project, which in turn used the data from Common Crawl and the Internet Archive.

Acknowledgement

We thank our collaborators at UONLP - The Natural Language Processing Group at the University of Oregon, and the computing resources of the managers of the Karolina Supercomputers. We also thank our friends at TurkuNLP for their support.

Data Breakdown:

There are 75 langauges, with the following breakdown:

Code Language # Documents # Documents (%) Size (GB)
0 en English 523,235,685 43.84 1244.39
1 zh Chinese 172,023,436 14.41 290.91
2 ru Russian 59,185,035 4.96 424.55
3 es Spanish 49,193,764 4.12 116.20
4 de German 35,204,652 2.95 78.32
5 fr French 33,063,792 2.77 69.66
6 ja Japanese 27,641,765 2.32 74.71
7 ko Korean 26,925,013 2.26 25.50
8 it Italian 22,396,067 1.88 48.30
9 pt Portuguese 18,367,640 1.54 39.09
10 th Thai 16,330,227 1.37 32.09
11 da Danish 13,547,169 1.13 18.40
12 sv Swedish 13,049,359 1.09 19.29
13 tr Turkish 12,659,104 1.06 29.14
14 nl Dutch 12,454,669 1.04 22.58
15 pl Polish 12,054,997 1.01 27.09
16 hu Hungarian 11,939,984 1.00 17.63
17 ro Romanian 11,578,945 0.97 18.57
18 hbs Serbo-Croatian 8,880,450 0.74 14.65
19 id Indonesian 8,473,141 0.71 16.23
20 bg Bulgarian 6,698,866 0.56 18.63
21 el Greek 6,674,496 0.56 29.61
22 ar Arabic 6,427,386 0.54 28.04
23 nb Norwegian Bokmål 5,925,942 0.50 10.14
24 fi Finnish 5,379,100 0.45 10.08
25 he Hebrew 5,320,279 0.45 12.06
26 uk Ukrainian 5,311,749 0.45 31.55
27 cs Czech 5,248,678 0.44 12.83
28 fa Persian 5,111,868 0.43 26.23
29 ms Malay 4,888,894 0.41 9.09
30 sk Slovak 4,758,917 0.40 5.50
31 ca Catalan 4,552,579 0.38 7.96
32 vi Vietnamese 4,493,567 0.38 16.95
33 hi Hindi 4,200,330 0.35 11.56
34 bn Bangla 2,785,980 0.23 4.76
35 lt Lithuanian 2,509,788 0.21 3.83
36 sl Slovenian 2,252,359 0.19 3.21
37 la Latin 2,147,688 0.18 1.42
38 et Estonian 1,754,719 0.15 2.88
39 az Azerbaijani 1,554,357 0.13 1.95
40 lv Latvian 1,469,245 0.12 2.19
41 ur Urdu 1,251,414 0.10 2.84
42 ta Tamil 1,128,321 0.09 7.21
43 gl Galician 1,101,337 0.09 1.31
44 sq Albanian 1,081,763 0.09 1.73
45 ne Nepali 860,657 0.07 1.91
46 mk Macedonian 641,111 0.05 1.61
47 af Afrikaans 636,976 0.05 0.77
48 tl Filipino 575,221 0.05 1.09
49 sw Swahili 571,247 0.05 0.60
50 eu Basque 559,194 0.05 0.67
51 is Icelandic 529,777 0.04 0.81
52 ka Georgian 524,645 0.04 1.48
53 hy Armenian 519,060 0.04 1.46
54 my Burmese 513,729 0.04 1.91
55 nn Norwegian Nynorsk 509,287 0.04 0.49
56 ml Malayalam 487,912 0.04 2.02
57 mn Mongolian 448,211 0.04 1.79
58 be Belarusian 426,194 0.04 1.48
59 uz Uzbek 423,865 0.04 1.19
60 mr Marathi 398,138 0.03 1.28
61 si Sinhala 337,785 0.03 1.55
62 te Telugu 279,240 0.02 1.00
63 kk Kazakh 274,770 0.02 1.07
64 mt Maltese 265,605 0.02 0.90
65 so Somali 261,100 0.02 0.24
66 gu Gujarati 242,074 0.02 0.74
67 kn Kannada 231,260 0.02 0.71
68 cy Welsh 179,157 0.02 0.20
69 ga Irish 134,796 0.01 0.15
70 tt Tatar 131,731 0.01 0.41
71 pa Punjabi 119,686 0.01 0.29
72 eo Esperanto 114,598 0.01 0.17
73 ps Pashto 99,783 0.01 0.23
74 ky Kyrgyz 86,551 0.01 0.31

Dataset structure

The dataset has a total of 6 columns, including:

  • 2 columns text, url will be the two main columns in this dataset.
  • the remaining columns id, document_lang, scores, langs belong to the original document in the HPLT V1.1 dataset, retained for debugging purposes. and will be removed in the future.

Therefore, when using, please only utilize the two columns text and url.

Process for Creating CulturaY

Firstly, to create CulturaY, we began with the HPLT dataset (version 1.1). This is also a notable difference between X and Y. While X was generated from cleaning data from Common Crawl (mC4, Oscar), Y was generated from cleaning raw data from the Internet Archive (HPLT). While Common Crawl is quite popular, data from the Internet Archive is less known and exploited, even though the data from both sources are similar. HPLT or CulturaY could be considered the first publicly released datasets originating from the Internet Archive. Using both CulturaX and CulturaY simultaneously will help your model have a more diverse source of data.

Our pipeline is built based on Bloom's data cleaning pipeline: evaluating each document in the dataset according to criteria such as document length, perplexity, bad words ratio, etc., and removing documents that do not perform well in any of these criteria. See our Blog for more details.

Citation

To cite CulturaY, please use:

@misc{nguyen2024culturay,
      title={CulturaY: A Large Cleaned Multilingual Dataset of 75 Languages}, 
      author={Thuat Nguyen, Huu Nguyen and Thien Nguyen},
      year={2024},
}
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