BramVanroy
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490daab
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Update README.md
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README.md
CHANGED
@@ -278,3 +278,257 @@ configs:
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- split: test
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path: 5B/test-*
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---
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- split: test
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path: 5B/test-*
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---
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+
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+
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+
## Filtering
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+
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+
The baseline ratios (punctuation, uppercase, digits) were calculated on the SONAR-500 corpus (excluding WRPEA WRPED WRUEA WRUED WRUEB).
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+
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**CulturaX**:
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- removed documents that contain the text "rechten voorbehouden" or "rights reserved"
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- remove document's whose URL contained "wikipedia.org" (because we include a cleaned version of Wikipedia ourselves)
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- removed documents that contain a "bad word" (see the section below)
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- removed documents that contain any non-latin characters. The idea is that "knowledge"-based information (e.g. original writing of a name) are allowed
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when the data comes from Wikipedia, but not from any other webcrawl, to avoid unsollicited noise.
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**CulturaX + Wikipedia**:
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- removed documents where ratio of punctuation marks vs. non-whitespace characters is higher than 0.2
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- removed documents where ratio of uppercase vs. non-whitespace characters is higher than 0.22
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- removed documents where ratio of digits vs. non-whitespace characters is higher than 0.16
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- removed documents where the average token length is < 2 or > 20
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## Bad words
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```python
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BAD_PHRASES_DOC_LEVEL = {
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# https://en.wikipedia.org/wiki/Dutch_profanity
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"achterlijk",
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"debiel",
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"downie",
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"idioot",
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"kankerlijer",
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"klere",
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"kolere",
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"minkukel",
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"pestkop",
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"pleuris",
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"pleuritis",
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"teringlijer",
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"tyfuslijer",
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"gadver",
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"getver",
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"godver",
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"godskolere",
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"godverork",
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"graftak",
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"kopvod",
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"verdomme",
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"anaalgeneraal",
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"bitch",
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"dikzak",
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"flikker",
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"fok",
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"fuck",
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"hoer",
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"klootzak",
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"klote",
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"kreng",
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"kringspiermusketier",
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"kut",
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"lamzak",
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"lul",
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"manwijf",
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"matennaai",
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"neuken",
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"neuker",
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"ouwehoer",
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"reet",
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"reetkever",
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"reetridder",
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"rotzak",
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"schijt",
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"shit",
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"slet",
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"slijmbal",
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"slons",
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"sodemieter",
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"stoephoer",
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"swaffel",
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"teef",
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"trut",
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"tut",
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"zak",
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"uilskuiken",
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"zeik",
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"bamivreter",
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"bosneger",
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"neger",
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"fransoos",
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"geitenneuker",
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"kaaskop",
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"kakker",
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"koelie",
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"lijp",
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"medelander",
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"mocro",
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"mof",
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"nikker",
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"poepchinees",
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"roetmop",
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"spaghettivreter",
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"loempiavouwer",
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"spanjool",
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"spleetoog",
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"tatta",
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"tokkie",
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"zandneger",
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"zwartzak",
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"halvezool",
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"kenau",
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"klootviool",
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"knuppel",
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"koekert",
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"koekwaus",
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"oelewapper",
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"smeerlap",
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"sukkel",
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"sul",
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"wappie",
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"wijf",
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"zooi",
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# xxx (a.o. https://gitlab.com/yhavinga/c4nlpreproc/-/blob/master/clean/badwords_ennl.py?ref_type=heads)
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"xxx",
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"anal",
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"blowjob",
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"buttplug",
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"cock",
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"cunt",
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"geil",
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"sex", # Standaardnederlands = seks, maybe we catch some porn or socialmedia sites with this misspelling
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"porn",
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# extra
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"nigger",
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"nigga",
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"hoerig",
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"klojo",
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}
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```
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## Config details
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`10k`
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- ratio_wikipedia: 100.00%
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- total_num_tokens: 10,078
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- train_num_tokens: 9,957
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- test_num_tokens: 121
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- total_num_samples: 38
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- train_num_samples: 37
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- test_num_samples: 1
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`100k`
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- ratio_wikipedia: 100.00%
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- total_num_tokens: 100,099
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- train_num_tokens: 99,537
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- test_num_tokens: 562
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- total_num_samples: 303
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- train_num_samples: 300
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- test_num_samples: 3
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`1M`
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- ratio_wikipedia: 100.00%
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- total_num_tokens: 1,000,104
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- train_num_tokens: 987,432
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- test_num_tokens: 12,672
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- total_num_samples: 2,722
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- train_num_samples: 2,695
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- test_num_samples: 27
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`10M`
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- ratio_wikipedia: 100.00%
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- total_num_tokens: 10,000,692
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- train_num_tokens: 9,905,387
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- test_num_tokens: 95,305
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- total_num_samples: 25,641
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- train_num_samples: 25,385
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- test_num_samples: 256
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`100M`
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- ratio_wikipedia: 100.00%
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- total_num_tokens: 100,000,049
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- train_num_tokens: 99,022,731
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- test_num_tokens: 977,318
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- total_num_samples: 237,578
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- train_num_samples: 235,203
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- test_num_samples: 2,375
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`1B`
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- ratio_wikipedia: 82.38%
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- total_num_tokens: 1,000,000,003
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- train_num_tokens: 990,064,856
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- test_num_tokens: 9,935,147
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- total_num_samples: 2,869,233
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- train_num_samples: 2,840,541
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- test_num_samples: 28,692
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`5B`
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- ratio_wikipedia: 35.62%
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- total_num_tokens: 5,000,000,224
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- train_num_tokens: 4,974,586,006
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- test_num_tokens: 25,414,218
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- total_num_samples: 12,603,939
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- train_num_samples: 12,539,939
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- test_num_samples: 64,000
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`10B`
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- ratio_wikipedia: 26.86%
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- total_num_tokens: 10,000,000,658
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- train_num_tokens: 9,973,803,589
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- test_num_tokens: 26,197,069
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- total_num_samples: 24,628,921
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- train_num_samples: 24,564,921
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- test_num_samples: 64,000
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`15B`
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- ratio_wikipedia: 23.85%
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- total_num_tokens: 15,000,001,092
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- train_num_tokens: 14,973,654,717
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- test_num_tokens: 26,346,375
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- total_num_samples: 36,653,903
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- train_num_samples: 36,589,903
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- test_num_samples: 64,000
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`20B`
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- ratio_wikipedia: 22.32%
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- total_num_tokens: 20,000,000,303
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- train_num_tokens: 19,973,764,973
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- test_num_tokens: 26,235,330
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- total_num_samples: 48,678,883
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- train_num_samples: 48,614,883
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- test_num_samples: 64,000
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`25B`
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- ratio_wikipedia: 21.40%
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- total_num_tokens: 25,000,000,737
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- train_num_tokens: 24,973,747,815
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- test_num_tokens: 26,252,922
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- total_num_samples: 60,703,865
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- train_num_samples: 60,639,865
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- test_num_samples: 64,000
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`30B`
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- ratio_wikipedia: 20.79%
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- total_num_tokens: 30,000,000,034
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- train_num_tokens: 29,973,830,841
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- test_num_tokens: 26,169,193
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- total_num_samples: 72,728,846
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- train_num_samples: 72,664,846
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- test_num_samples: 64,000
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`35B`
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- ratio_wikipedia: 20.35%
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- total_num_tokens: 35,000,000,468
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- train_num_tokens: 34,973,480,399
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- test_num_tokens: 26,520,069
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- total_num_samples: 84,753,828
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- train_num_samples: 84,689,828
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- test_num_samples: 64,000
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