Datasets:
File size: 18,133 Bytes
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"detail": "59 files hashed; 0 changed, 0 added, 0 removed",
"id": "A1",
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"files": 59
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"seconds": 253.0,
"status": "PASS",
"title": "Rebuild is byte-identical"
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"detail": "59/59 files verified against v1.json (0 mismatched, 0 missing)",
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"status": "PASS",
"title": "`data.fetch --verify-only` passes"
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"PubMed Central": 27000000,
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"seconds": 0.0,
"status": "PASS",
"title": "Token counts per subject and half"
},
{
"detail": "worst deviation 0.416 points across 598 overlapping windows (stride 250,000), tolerance 2.0",
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"numbers": {
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"status": "PASS",
"title": "Shares in every 1,000,000-token window"
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{
"detail": "train.bin: 150,475,264 tokens, 332,886 segments, 333,027 EOT separator/pad tokens, max id 50256 | label.bin: 15,021,806 tokens, 13,306 segments, 13,305 EOT separator/pad tokens, max id 50256 | test.bin: 15,023,952 tokens, 13,381 segments, 13,380 EOT separator/pad tokens, max id 50256",
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"status": "PASS",
"title": "Format: dtype, vocab bound, EOT, index tiling"
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{
"detail": "1,000 random segments checked token for token (820 of them whole documents, also compared as text); 0 mismatches",
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"sampled": 1000,
"whole_documents": 820
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"seconds": 2.8,
"status": "PASS",
"title": "Decoding index segments reproduces the source"
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{
"detail": "ids disjoint across train/label/test; 0 exact-hash matches; 0 documents over 50%; worst single document 50.0%; aggregates Pile-CC=0.64%, Github=14.35%, PubMed=2.93%, FreeLaw=9.21%, Wikipedia=2.14%, USPTO=0.00%",
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"test": 13381,
"train": 113247
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"seconds": 88.3,
"status": "PASS",
"title": "Leaks: ids, exact hashes, 13-gram overlap"
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"detail": "halves share 0 documents; smallest half/subject is 708 documents (minimum 500); longest document 4096 tokens (cap 4096)",
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"USPTO Backgrounds": 3084,
"Wikipedia (en)": 3687
}
},
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"seconds": 0.0,
"status": "PASS",
"title": "Halves: disjoint, >=500 docs, <=4096 tokens"
},
{
"detail": "['USPTO Backgrounds'] appear in 0 train.bin segments by document id and 0 by subject label; train.bin carries ['FreeLaw', 'Github', 'Pile-CC', 'PubMed Central', 'Wikipedia (en)', 'bio']",
"id": "A9",
"numbers": {
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"segments": 0
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"status": "PASS",
"title": "No held-out-only subject in train.bin"
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{
"detail": "142,886 Pile segments: index subject == raw-archive meta.pile_set_name == the document id's slug; 190,000 biography segments all labelled `bio` with a known person id",
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"numbers": {
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"problems": [],
"raw_documents": 177718
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"seconds": 4.9,
"status": "PASS",
"title": "Subject labels agree with the source"
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"detail": "accuracy 94.87% on 13,381 test-half documents (threshold 90%); per subject Pile-CC=89.7%, Github=97.8%, PubMed=97.6%, FreeLaw=99.1%, Wikipedia=95.0%, USPTO=96.2%",
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"status": "PASS",
"title": "Bag-of-words subject classifier (sanity)"
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{
"detail": "2,500 people, names unique and absent from the Pile, genders {'female': 1250, 'male': 1250}, 5 facts each; first-token uniqueness holds per list (first two for birth_date, which has only 12 distinct first tokens); chi-square p birth_date=0.124, birth_city=0.877, university=0.183, major=0.940, employer=0.347",
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"male": 1250
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"employer": 0.347052,
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"people": 2500,
"tokens": {
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"prefix_tokens": 1,
"unique": true,
"values": 200
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"birth_date": {
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"prefix_tokens": 2,
"unique": true,
"values": 200
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"employer": {
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"prefix_tokens": 1,
"unique": true,
"values": 250
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"major": {
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"prefix_tokens": 1,
"unique": true,
"values": 100
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"university": {
"distinct_first": 300,
"prefix_tokens": 1,
"unique": true,
"values": 300
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"status": "PASS",
"title": "Biography facts"
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{
"detail": "100,000 rows: **0** leak the value verbatim (0), **0** via the person's name (0), **0** via another of the person's values (0); 50,000 training prompts are exact prefixes of their biography; 50,000 paraphrase prompts, 200 of them searched in full against train.bin and absent; held-out markers inside biography text: 'Question:'=0, 'When it comes to'=0, 'is on record as'=0, 'reads as follows'=0 (the same markers occur 571 times in ordinary Pile text, which is not a leak); REPORTED: 48 rows whose ranking key is a TEMPLATE word (birth_city=Thessaloniki, Greece, employer=Heineken, major=Theology, university=Aalborg University)",
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"leak_via_name": [],
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"n_leak_value_verbatim": 0,
"n_leak_via_name": 0,
"n_leak_via_other_value": 0,
"paraphrase_prompts": 50000,
"pile_marker_hits": {
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"When it comes to": 275,
"is on record as": 2,
"reads as follows": 192
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"rows": 100000,
"template_word_rows": 48,
"template_word_values": {
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"employer=Heineken": 17,
"major=Theology": 20,
"university=Aalborg University": 5
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"seconds": 8.0,
"status": "PASS",
"title": "Fact prompts: no answer leaks"
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{
"detail": "190,000 copies over 2,000 trained people, every count equal to its tier target and spread over the 4 rewordings; 0 cross a 512-token boundary; 0 of 500 control names appear in train text",
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"numbers": {
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"copies": 190000,
"crossing": 0,
"people_with_copies": 2000
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"seconds": 3.4,
"status": "PASS",
"title": "Exposure counts and control isolation"
},
{
"detail": "random scorer: mean rank fraction 0.502, top-1 0.558% over 36,000 prompts; untrained model: 0.501, top-1 0.525% over 4,000; mean candidate list 210",
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"mean_margin": -2.7352,
"mean_rank": 105.448,
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"median_rank": 92.0,
"n": 36000,
"top1": 0.005583
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"rank_fraction_by_attribute": {
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"random/birth_date": 0.504117,
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"untrained/employer": 0.499975,
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"mean_margin": -1.1695,
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"median_rank": 92.0,
"n": 4000,
"top1": 0.00525
}
},
"seconds": 10.0,
"status": "PASS",
"title": "Probe floor: random and untrained sit mid-list"
},
{
"detail": "293,896 sequences of 512; same seed reproduces the order, a different seed does not, the order is a permutation, and a resume from (seed, position) matches an unbroken run",
"id": "A16",
"numbers": {
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"resume_position": 12
},
"seconds": 0.1,
"status": "PASS",
"title": "Loader: order, resume, shapes"
},
{
"detail": "Pile-CC: model 6.7886 vs unigram 7.559; Github: model 5.7371 vs unigram 6.3888; PubMed: model 6.5792 vs unigram 7.4554; FreeLaw: model 5.8735 vs unigram 6.8493; Wikipedia: model 7.0163 vs unigram 7.72; USPTO: model 7.0021 vs unigram 7.9605",
"id": "A17",
"numbers": {
"FreeLaw": {
"counts_from": "own training text",
"smoke_run_loss": 5.8735,
"tokens": 2502989,
"unigram_cross_entropy": 6.8493
},
"Github": {
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"smoke_run_loss": 5.7371,
"tokens": 2502662,
"unigram_cross_entropy": 6.3888
},
"Pile-CC": {
"counts_from": "own training text",
"smoke_run_loss": 6.7886,
"tokens": 2501855,
"unigram_cross_entropy": 7.559
},
"PubMed Central": {
"counts_from": "own training text",
"smoke_run_loss": 6.5792,
"tokens": 2502199,
"unigram_cross_entropy": 7.4554
},
"USPTO Backgrounds": {
"counts_from": "pooled 5 subjects",
"smoke_run_loss": 7.0021,
"tokens": 2500283,
"unigram_cross_entropy": 7.9605
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"Wikipedia (en)": {
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"smoke_run_loss": 7.0163,
"tokens": 2500584,
"unigram_cross_entropy": 7.72
}
},
"seconds": 7.0,
"status": "PASS",
"title": "Model beats the per-subject unigram baseline"
},
{
"detail": "5,830 steps / 96M tokens in 2.03 h of training. test top-1: frequent 40.5%, normal 3.1%, rare 0.8%, control 0.6% (frequent/control = 64.003x, needs 2x; monotone yes). paraphrase top-1: frequent 2.2%, control 0.4%",
"id": "A18",
"numbers": {
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"tokens_seen": 95518720,
"verdict": {
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"frequent": 0.405333,
"pass": true,
"ratio": 64.003
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"monotone_frequent_normal_rare": {
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},
"paraphrase_top1": {
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"frequent": 0.021667,
"normal": 0.006833,
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},
"pass": true,
"test_top1": {
"control": 0.006333,
"frequent": 0.405333,
"normal": 0.031,
"rare": 0.008
}
}
},
"seconds": 0.0,
"status": "PASS",
"title": "Biography facts are learnable"
}
],
"fingerprints": {
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"pack": "15643c90477c31a7cbc5e394b1f353d795bb417ad6a5ef656b772ebbc1e91e81",
"pile": "3f4303d9b926b730d8d9bd9269084c6052df66b63aece15a07af100866aa2984"
},
"revision": "3be90335b66f24456a5d6659d9c8d208c0357119",
"version": "v1"
}
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