metadata

language:
  - nl
size_categories:
  - 10B<n<100B
task_categories:
  - text-generation
  - text2text-generation
pretty_name: Filtered CulturaX + Wikipedia for Dutch
dataset_info:
  - config_name: 100M
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
        num_bytes: 738455828.5851797
        num_examples: 1018200
      - name: test
        num_bytes: 7458534.414820259
        num_examples: 10284
    download_size: 411183119
    dataset_size: 745914363
  - config_name: 100k
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
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        num_bytes: 745955.3074739829
        num_examples: 1047
      - name: test
        num_bytes: 7124.692526017029
        num_examples: 10
    download_size: 366788
    dataset_size: 753080
  - config_name: 10B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
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        num_examples: 40176566
      - name: test
        num_bytes: 105996030.65543362
        num_examples: 64000
    download_size: 42132184504
    dataset_size: 66645941677
  - config_name: 10M
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
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        num_examples: 139851
      - name: test
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        num_examples: 1412
    download_size: 37995388
    dataset_size: 77508895
  - config_name: 10k
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
        num_bytes: 72048.30379746835
        num_examples: 78
      - name: test
        num_bytes: 5896
        num_examples: 1
    download_size: 47197
    dataset_size: 77944.30379746835
  - config_name: 15B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
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        num_examples: 59584123
      - name: test
        num_bytes: 107121206.74724333
        num_examples: 64000
    download_size: 63139415312
    dataset_size: 99837170562
  - config_name: 1B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
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      - name: train
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      - name: test
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    download_size: 4260450464
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  - config_name: 1M
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
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        num_examples: 10694
      - name: test
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        num_examples: 108
    download_size: 3845466
    dataset_size: 7517830
  - config_name: 20B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
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        num_examples: 78991679
      - name: test
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        num_examples: 64000
    download_size: 84141456153
    dataset_size: 133028398305
  - config_name: 25B
    features:
      - name: text
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      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
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        num_examples: 98399236
      - name: test
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        num_examples: 64000
    download_size: 105147418131
    dataset_size: 166219627190
  - config_name: 30B
    features:
      - name: text
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      - name: url
        dtype: string
      - name: source
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    splits:
      - name: train
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      - name: test
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        num_examples: 64000
    download_size: 126152714564
    dataset_size: 199410856075
  - config_name: 35B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
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        num_examples: 137214350
      - name: test
        num_bytes: 108440503.81899258
        num_examples: 64000
    download_size: 147149925109
    dataset_size: 232602084960
  - config_name: 40B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
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        num_examples: 156621907
      - name: test
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        num_examples: 64000
    download_size: 168152290262
    dataset_size: 265793313845
  - config_name: 45B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
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        num_examples: 176029463
      - name: test
        num_bytes: 108663946.60903454
        num_examples: 64000
    download_size: 189159571162
    dataset_size: 298984541588
  - config_name: 50B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
        num_bytes: 332067028077.12775
        num_examples: 195437020
      - name: test
        num_bytes: 108742395.87226707
        num_examples: 64000
    download_size: 210160621183
    dataset_size: 332175770473
  - config_name: 55B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
        num_bytes: 365258192681.75964
        num_examples: 214844577
      - name: test
        num_bytes: 108806676.24034382
        num_examples: 64000
    download_size: 231164757019
    dataset_size: 365366999358
  - config_name: 5B
    features:
      - name: text
        dtype: string
      - name: url
        dtype: string
      - name: source
        dtype: string
    splits:
      - name: train
        num_bytes: 33351938314.309906
        num_examples: 20769009
      - name: test
        num_bytes: 102774477.69009268
        num_examples: 64000
    download_size: 21119808690
    dataset_size: 33454712792
configs:
  - config_name: 100M
    data_files:
      - split: train
        path: 100M/train-*
      - split: test
        path: 100M/test-*
  - config_name: 100k
    data_files:
      - split: train
        path: 100k/train-*
      - split: test
        path: 100k/test-*
  - config_name: 10B
    data_files:
      - split: train
        path: 10B/train-*
      - split: test
        path: 10B/test-*
  - config_name: 10M
    data_files:
      - split: train
        path: 10M/train-*
      - split: test
        path: 10M/test-*
  - config_name: 10k
    data_files:
      - split: train
        path: 10k/train-*
      - split: test
        path: 10k/test-*
  - config_name: 15B
    data_files:
      - split: train
        path: 15B/train-*
      - split: test
        path: 15B/test-*
  - config_name: 1B
    data_files:
      - split: train
        path: 1B/train-*
      - split: test
        path: 1B/test-*
  - config_name: 1M
    data_files:
      - split: train
        path: 1M/train-*
      - split: test
        path: 1M/test-*
  - config_name: 20B
    data_files:
      - split: train
        path: 20B/train-*
      - split: test
        path: 20B/test-*
  - config_name: 25B
    data_files:
      - split: train
        path: 25B/train-*
      - split: test
        path: 25B/test-*
  - config_name: 30B
    data_files:
      - split: train
        path: 30B/train-*
      - split: test
        path: 30B/test-*
  - config_name: 35B
    data_files:
      - split: train
        path: 35B/train-*
      - split: test
        path: 35B/test-*
  - config_name: 40B
    data_files:
      - split: train
        path: 40B/train-*
      - split: test
        path: 40B/test-*
  - config_name: 45B
    data_files:
      - split: train
        path: 45B/train-*
      - split: test
        path: 45B/test-*
  - config_name: 50B
    data_files:
      - split: train
        path: 50B/train-*
      - split: test
        path: 50B/test-*
  - config_name: 55B
    data_files:
      - split: train
        path: 55B/train-*
      - split: test
        path: 55B/test-*
  - config_name: 5B
    data_files:
      - split: train
        path: 5B/train-*
      - split: test
        path: 5B/test-*

Filtered CulturaX + Wikipedia for Dutch

This is a combined and filtered version of CulturaX and Wikipedia, only including Dutch. It is intended for the training of LLMs.

Different configs are available based on the number of tokens (see a section below with an overview). This can be useful if you want to know exactly how many tokens you have. Great for using as a streaming dataset, too. Tokens are counted as white-space tokens, so depending on your tokenizer, you'll likely end up with more tokens than indicated here.

Every config also has a test set (for validation) of 1% the total size of the dataset, minimally 1 max. 64k samples (~16M tokens).

Wikipedia and CulturaX were suffled before merging and the teset set creation was also shuffled. Priority is given to Wikipedia to prioritize knowledge-content, so the smaller configs will consist exclusively of Wikipedia and for the larger configs we augment with CulturaX. Every config builds further on the previous, so this means that every config contains the same data as the smaller ones and more HOWEVER their train/test splits are not the same, so test set of one config may overlap with samples for another training set. This is usually not a problem but just be aware that you do not train on one config's training set and test with another config's test set.

Configs

`10k` -- 79 samples -- 10,087 tokens

ratio_wikipedia: 100.00%
total_num_tokens: 10,087
train_num_tokens: 9,205
test_num_tokens: 882
total_num_samples: 79
train_num_samples: 78
test_num_samples: 1

`100k` -- 1,057 samples -- 100,075 tokens

ratio_wikipedia: 100.00%
total_num_tokens: 100,075
train_num_tokens: 98,044
test_num_tokens: 2,031
total_num_samples: 1,057
train_num_samples: 1,047
test_num_samples: 10

`1M` -- 10,802 samples -- 1,000,239 tokens

ratio_wikipedia: 100.00%
total_num_tokens: 1,000,239
train_num_tokens: 991,119
test_num_tokens: 9,120
total_num_samples: 10,802
train_num_samples: 10,694
test_num_samples: 108

`10M` -- 141,263 samples -- 10,000,022 tokens

ratio_wikipedia: 100.00%
total_num_tokens: 10,000,022
train_num_tokens: 9,874,772
test_num_tokens: 125,250
total_num_samples: 141,263
train_num_samples: 139,851
test_num_samples: 1,412

`100M` -- 1,028,484 samples -- 100,000,047 tokens

ratio_wikipedia: 100.00%
total_num_tokens: 100,000,047
train_num_tokens: 99,013,372
test_num_tokens: 986,675
total_num_samples: 1,028,484
train_num_samples: 1,018,200
test_num_samples: 10,284

`1B` -- 5,153,898 samples -- 1,000,000,187 tokens

ratio_wikipedia: 61.21%
total_num_tokens: 1,000,000,187
train_num_tokens: 989,990,190
test_num_tokens: 10,009,997
total_num_samples: 5,153,898
train_num_samples: 5,102,360
test_num_samples: 51,538

`5B` -- 20,833,009 samples -- 5,000,000,076 tokens

ratio_wikipedia: 25.35%
total_num_tokens: 5,000,000,076
train_num_tokens: 4,984,493,654
test_num_tokens: 15,506,422
total_num_samples: 20,833,009
train_num_samples: 20,769,009
test_num_samples: 64,000

`10B` -- 40,240,566 samples -- 10,000,000,115 tokens

ratio_wikipedia: 18.41%
total_num_tokens: 10,000,000,115
train_num_tokens: 9,984,156,828
test_num_tokens: 15,843,287
total_num_samples: 40,240,566
train_num_samples: 40,176,566
test_num_samples: 64,000

`15B` -- 59,648,123 samples -- 15,000,000,154 tokens

ratio_wikipedia: 15.98%
total_num_tokens: 15,000,000,154
train_num_tokens: 14,983,970,518
test_num_tokens: 16,029,636
total_num_samples: 59,648,123
train_num_samples: 59,584,123
test_num_samples: 64,000

`20B` -- 79,055,679 samples -- 20,000,000,009 tokens

ratio_wikipedia: 14.75%
total_num_tokens: 20,000,000,009
train_num_tokens: 19,983,799,357
test_num_tokens: 16,200,652
total_num_samples: 79,055,679
train_num_samples: 78,991,679
test_num_samples: 64,000

`25B` -- 98,463,236 samples -- 25,000,000,048 tokens

ratio_wikipedia: 14.00%
total_num_tokens: 25,000,000,048
train_num_tokens: 24,983,765,326
test_num_tokens: 16,234,722
total_num_samples: 98,463,236
train_num_samples: 98,399,236
test_num_samples: 64,000

`30B` -- 117,870,793 samples -- 30,000,000,087 tokens

ratio_wikipedia: 13.50%
total_num_tokens: 30,000,000,087
train_num_tokens: 29,983,707,932
test_num_tokens: 16,292,155
total_num_samples: 117,870,793
train_num_samples: 117,806,793
test_num_samples: 64,000

`35B` -- 137,278,350 samples -- 35,000,000,126 tokens

ratio_wikipedia: 13.14%
total_num_tokens: 35,000,000,126
train_num_tokens: 34,983,914,739
test_num_tokens: 16,085,387
total_num_samples: 137,278,350
train_num_samples: 137,214,350
test_num_samples: 64,000

`40B` -- 156,685,907 samples -- 40,000,000,165 tokens

ratio_wikipedia: 12.87%
total_num_tokens: 40,000,000,165
train_num_tokens: 39,983,508,625
test_num_tokens: 16,491,540
total_num_samples: 156,685,907
train_num_samples: 156,621,907
test_num_samples: 64,000

`45B` -- 176,093,463 samples -- 45,000,000,020 tokens

ratio_wikipedia: 12.66%
total_num_tokens: 45,000,000,020
train_num_tokens: 44,983,608,118
test_num_tokens: 16,391,902
total_num_samples: 176,093,463
train_num_samples: 176,029,463
test_num_samples: 64,000

`50B` -- 195,501,020 samples -- 50,000,000,059 tokens

ratio_wikipedia: 12.49%
total_num_tokens: 50,000,000,059
train_num_tokens: 49,983,567,461
test_num_tokens: 16,432,598
total_num_samples: 195,501,020
train_num_samples: 195,437,020
test_num_samples: 64,000

`55B` -- 214,908,577 samples -- 55,000,000,098 tokens

ratio_wikipedia: 12.35%
total_num_tokens: 55,000,000,098
train_num_tokens: 54,983,723,278
test_num_tokens: 16,276,820
total_num_samples: 214,908,577
train_num_samples: 214,844,577
test_num_samples: 64,000

Filtering

While CultruaX already has done a lot of filtering, some more filtering can be done to improve the quality of the corpus. These filters are described below.

The baseline ratios (punctuation, uppercase, digits) were calculated on the SONAR-500 corpus (excluding WRPEA WRPED WRUEA WRUED WRUEB).

CulturaX:

removed documents that contain the text "rechten voorbehouden" or "rights reserved"
remove documents whose URL contained "wikipedia.org" (because we include a cleaned version of Wikipedia ourselves)
removed documents that contain a "bad word" (see the section below)
removed documents that contain any non-latin characters. The idea is that "knowledge"-based information (e.g. original writing of a name) are allowed when the data comes from Wikipedia, but not from any other webcrawl, to avoid unsollicited noise.

CulturaX + Wikipedia:

removed documents where ratio of punctuation marks vs. non-whitespace characters is higher than 0.2
removed documents where ratio of uppercase vs. non-whitespace characters is higher than 0.22
removed documents where ratio of digits vs. non-whitespace characters is higher than 0.16
removed documents where the average token length is < 2 or > 20

Bad words

BAD_PHRASES_DOC_LEVEL = {
    # https://en.wikipedia.org/wiki/Dutch_profanity
    "achterlijk",
    "debiel",
    "downie",
    "idioot",
    "kankerlijer",
    "klere",
    "kolere",
    "minkukel",
    "pestkop",
    "pleuris",
    "pleuritis",
    "teringlijer",
    "tyfuslijer",
    "gadver",
    "getver",
    "godver",
    "godskolere",
    "godverork",
    "graftak",
    "kopvod",
    "verdomme",
    "anaalgeneraal",
    "bitch",
    "dikzak",
    "flikker",
    "fok",
    "fuck",
    "hoer",
    "klootzak",
    "klote",
    "kreng",
    "kringspiermusketier",
    "kut",
    "lamzak",
    "lul",
    "manwijf",
    "matennaai",
    "neuken",
    "neuker",
    "ouwehoer",
    "reet",
    "reetkever",
    "reetridder",
    "rotzak",
    "schijt",
    "shit",
    "slet",
    "slijmbal",
    "slons",
    "sodemieter",
    "stoephoer",
    "swaffel",
    "teef",
    "trut",
    "tut",
    "zak",
    "uilskuiken",
    "zeik",
    "bamivreter",
    "bosneger",
    "neger",
    "fransoos",
    "geitenneuker",
    "kaaskop",
    "kakker",
    "koelie",
    "lijp",
    "medelander",
    "mocro",
    "mof",
    "nikker",
    "poepchinees",
    "roetmop",
    "spaghettivreter",
    "loempiavouwer",
    "spanjool",
    "spleetoog",
    "tatta",
    "tokkie",
    "zandneger",
    "zwartzak",
    "halvezool",
    "kenau",
    "klootviool",
    "knuppel",
    "koekert",
    "koekwaus",
    "oelewapper",
    "smeerlap",
    "sukkel",
    "sul",
    "wappie",
    "wijf",
    "zooi",
    # xxx (a.o. https://gitlab.com/yhavinga/c4nlpreproc/-/blob/master/clean/badwords_ennl.py?ref_type=heads)
    "xxx",
    "anal",
    "blowjob",
    "buttplug",
    "cock",
    "cunt",
    "geil",
    "sex",  # Standaardnederlands = seks, maybe we catch some porn or socialmedia sites with this misspelling
    "porn",
    # extra
    "nigger",
    "nigga",
    "hoerig",
    "klojo",
}

Config details

License information

For CulturaX: https://huggingface.co/datasets/uonlp/CulturaX#license-information For Wikipedia: https://huggingface.co/datasets/wikimedia/wikipedia#licensing-information

Filtered CulturaX + Wikipedia for Dutch

Configs

10k -- 79 samples -- 10,087 tokens

100k -- 1,057 samples -- 100,075 tokens

1M -- 10,802 samples -- 1,000,239 tokens

10M -- 141,263 samples -- 10,000,022 tokens

100M -- 1,028,484 samples -- 100,000,047 tokens

1B -- 5,153,898 samples -- 1,000,000,187 tokens

5B -- 20,833,009 samples -- 5,000,000,076 tokens

10B -- 40,240,566 samples -- 10,000,000,115 tokens

15B -- 59,648,123 samples -- 15,000,000,154 tokens

20B -- 79,055,679 samples -- 20,000,000,009 tokens

25B -- 98,463,236 samples -- 25,000,000,048 tokens

30B -- 117,870,793 samples -- 30,000,000,087 tokens

35B -- 137,278,350 samples -- 35,000,000,126 tokens

40B -- 156,685,907 samples -- 40,000,000,165 tokens

45B -- 176,093,463 samples -- 45,000,000,020 tokens

50B -- 195,501,020 samples -- 50,000,000,059 tokens

55B -- 214,908,577 samples -- 55,000,000,098 tokens