Dontopedia

Training run anchor_G16_20K

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

Training run anchor_G16_20K has 590 facts recorded in Dontopedia across 99 references, with 56 live disagreements.

590 facts·441 predicates·99 sources·56 in dispute

Mostly:has total steps(17), rdf:type(17), total steps(12)

Maturity scale raw canonical shape-checked rule-derived certified

Has Total Stepsin disputehasTotalSteps

  • 2000[8]all time · Part 3
  • 16670[23]all time · Part 130
  • 16670[24]all time · Part 133
  • 16670[26]all time · Part 140
  • 16684[27]all time · Part 150
  • 16684[28]all time · Part 155
  • 12432[38]all time · Part 239
  • 6216[40]all time · Part 238
  • 12432[43]all time · Part 247
  • 20000[47]all time · Part 331

Rdf:typein disputerdf:type

Total Stepsin disputetotalSteps

  • 16670[21]all time · Part 125
  • 16670[25]all time · Part 136
  • 1000[31]all time · Part 210
  • 1000[36]all time · Part 230
  • 20000[48]all time · Part 336
  • 20000[50]all time · Part 372
  • 16670[80]sourceall time · 127
  • 16684[82]sourceall time · 158
  • 1000[84]sourceall time · 189
  • 1000[85]sourceall time · 209

Inbound mentions (75)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

belongsToBelongs to(7)

partOfTrainingPart of Training(3)

hasNoNaNHas No Na N(2)

potentiallyUsedInPotentially Used in(2)

reportsProgressReports Progress(2)

achievedLowestBPBAchieved Lowest Bpb(1)

activeMidTrainingActive Mid Training(1)

advocatesContinuationAdvocates Continuation(1)

aimsAtLowPerplexityAims at Low Perplexity(1)

announcesCompletionAnnounces Completion(1)

announcesDecisionToStopAnnounces Decision to Stop(1)

announcesSectionAnnounces Section(1)

announcesTrainingCompleteAnnounces Training Complete(1)

buildsInParallelBuilds in Parallel(1)

commentedOnCommented on(1)

considersAchievableConsiders Achievable(1)

correlatesWithLossCorrelates With Loss(1)

decreasesOverTimeIdeallyDecreases Over Time Ideally(1)

demonstratesLearningProgressDemonstrates Learning Progress(1)

demonstratesOptimizationsDemonstrates Optimizations(1)

describesDescribes(1)

didNotKillNarrativeCapabilityDid Not Kill Narrative Capability(1)

existentiallyCommittedExistentially Committed(1)

expandedLexiconOfExpanded Lexicon of(1)

expressesFrustrationWithHungRunExpresses Frustration With Hung Run(1)

firedFired(1)

generatedByTextGenerated by Text(1)

hasBestLossSoFarHas Best Loss So Far(1)

hasNoProblemHas No Problem(1)

hasUntappedPotentialHas Untapped Potential(1)

indicatesFailureIndicates Failure(1)

intendsToLaunchIntends to Launch(1)

interpretsAsStableLearningInterprets As Stable Learning(1)

isDatasetForIs Dataset for(1)

isEnabledPostOptimizationIs Enabled Post Optimization(1)

isMinimumLossSoFarIs Minimum Loss So Far(1)

isPartOfIs Part of(1)

isPrimaryMetricIs Primary Metric(1)

isTrainedEntityIs Trained Entity(1)

isWatchingTrainingRunIs Watching Training Run(1)

knowsBs4CapabilityKnows Bs4 Capability(1)

lacksProblemsLacks Problems(1)

monitorsTrainingMonitors Training(1)

neverBeatenNever Beaten(1)

optimizesTrainingOptimizes Training(1)

partOfPart of(1)

performanceOfPerformance of(1)

performsStatusUpdatePerforms Status Update(1)

plansRestartPlans Restart(1)

postsTrainingLogPosts Training Log(1)

presupposesExistenceOfPresupposes Existence of(1)

presupposesLogicFixesNeededPresupposes Logic Fixes Needed(1)

presupposesOngoingPresupposes Ongoing(1)

presupposesOngoingProcessPresupposes Ongoing Process(1)

reportsContinuingFullEpochReports Continuing Full Epoch(1)

reportsStatusOfReports Status of(1)

reportsTrainingProgressReports Training Progress(1)

reworkedReworked(1)

setEarlySet Early(1)

sharesProgressUpdateShares Progress Update(1)

sharesProgressUpdatesShares Progress Updates(1)

showcasesQualityShowcases Quality(1)

terminatedTrainingTerminated Training(1)

wasUsedDuringWas Used During(1)

Other facts (543)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

543 facts
PredicateValueRef
Has Sequence Length1024[34]
Has Sequence Length2048[47]
Has Sequence Length512[48]
Has Sequence Length8192[58]
Has Sequence Length2048[86]
Has Sequence Length128[95]
Has Batch Size4[34]
Has Batch Size16[40]
Has Batch Size8[47]
Has Batch Size64[48]
Has Batch Size64[58]
Has Batch Size8[86]
Has Step4000[51]
Has Step25/1245[56]
Has Step1000[68]
Has Step100[85]
Has Step200[85]
Has Step300[85]
Has Learning Rate0.0001[40]
Has Learning Rate3e-04[47]
Has Learning Rate0.0000129[82]
Has Learning Rate0.0001[86]
Has Learning Rate0.0005[95]
Has Metric Value9.3[90]
Has Metric Value55.7[90]
Has Metric Value61[90]
Has Metric Value64.4[90]
Has Metric Value67.8[90]
Has Bpb Value3.583[90]
Has Bpb Value3.328[90]
Has Bpb Value3.183[90]
Has Bpb Value3.096[90]
Has Bpb Value3.05[90]
Has Warmup Steps500[40]
Has Warmup Steps500[47]
Has Warmup Steps50[58]
Has Warmup Steps300[86]
Has Loss1.494[48]
Has Loss4.9122[56]
Has Loss0.3609[63]
Has Loss0.9332[68]
Time Elapsed32s[85]
Time Elapsed64s[85]
Time Elapsed97s[85]
Time Elapsed1.7[88]
Presupposes OngoingLanguage Model[10]
Presupposes OngoingTraining Run[22]
Presupposes Ongoingnull[52]
Has Best Loss1.5656[15]
Has Best Loss6.04[75]
Has Best Loss3.6777[76]
Is Complete50,000/50,000 iters[15]
Is Completetrue[38]
Is CompleteYes[61]
Has Elapsed Time~2.5 hours[18]
Has Elapsed Time268s[33]
Has Elapsed Time303s[33]
Is OngoingAt Step 6000[23]
Is OngoingTraining[28]
Is Ongoingtrue[47]
Has Ppl at Step2216.6[33]
Has Ppl at Step2789.1[33]
Has Ppl at Step2732.6[33]
Has Tok Per S12074[33]
Has Tok Per S12062[33]
Has Tok Per S13611[63]
Has Lite Phasefalse[40]
Has Lite Phasefalse[47]
Has Lite Phasefalse[86]
Tokens Per Second98782[48]
Tokens Per Second13027[85]
Tokens Per Second13186[85]
Has Lr0.0000943[48]
Has Lr0.0000916[51]
Has Lr9.00e-05[63]
Batch Size64[50]
Batch Size4[80]
Batch Size64[92]
Sequence Length256[50]
Sequence Length2048[80]
Sequence Length256[92]
Has Bpb2.444[51]
Has Bpb0.521[63]
Has Bpb1.3463[68]
Loss at Step11.6429[85]
Loss at Step11.7602[85]
Loss at Step11.5419[85]
Ppl at Step113884.2[85]
Ppl at Step128058.6[85]
Ppl at Step102939.2[85]
Sys R at Step0.345[85]
Sys R at Step0.331[85]
Sys R at Step0.348[85]
Has ModalityText Modality[86]
Has ModalityImage Modality[86]
Has ModalityAudio Modality[86]
Lacks Observation of35K-step cliff[97]
Lacks Observation ofgnorm explosion[97]
Lacks Observation ofcatastrophic forgetting[97]
Has Final Val Loss3.7805[3]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

existsPubliclyblah/general/part-119
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3.7141
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5000
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100000
reachedItersblah/watt-activation/part-32
57K
corpusContaminationblah/watt-activation/part-32
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onTrackblah/watt-activation/part-32
true
totalItersblah/watt-activation/part-39
139000
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~30 min
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hasBestLossblah/watt-activation/part-33
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null
achievedBestLossAtIterationblah/watt-activation/part-33
29630
isCompleteblah/watt-activation/part-33
50,000/50,000 iters
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null
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null
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currentlyOngoingblah/watt-activation/part-94
true
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doesNotResumeIteratorStateblah/watt-activation/part-91
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hasPeakMemoryblah/watt-activation/part-91
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recoveredPastPreviousBestblah/watt-activation/part-91
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hasZeroMemoryDriftblah/watt-activation/part-91
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resumesFromblah/watt-activation/part-91
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resumesModelWeightsblah/watt-activation/part-91
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experiencedHitOnResumeblah/watt-activation/part-91
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hasIterationSpeedblah/watt-activation/part-91
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hasGlobalItersblah/watt-activation/part-91
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isSteadilyPushingLowerblah/watt-activation/part-91
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maintainsStableThroughputblah/watt-activation/part-91
ex:true
hasElapsedTimeblah/watt-activation/part-91
~2.5 hours
hasCompletedItersSinceResumeblah/watt-activation/part-91
6000
hasCompletedItersblah/watt-activation/part-91
10000
hasCompletedEpochsblah/watt-activation/part-91
0.31
occursOnMacStudioblah/watt-activation/part-98
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presupposesOngoingStatusblah/watt-activation/part-95
null
teleologicallyAimsForEpochCompletionblah/watt-activation/part-95
null
hasRemainingTimeblah/watt-activation/part-95
5
isApproachingblah/watt-activation/part-95
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totalStepsblah/watt-activation/part-125
16670
hasDataPositionblah/watt-activation/part-127
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presupposesOngoingblah/watt-activation/part-127
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progressesFromblah/watt-activation/part-127
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aimsAtLowPerplexityblah/watt-activation/part-127
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resumedFromStepblah/watt-activation/part-127
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hasTeleologicalGoalblah/watt-activation/part-130
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16670
isOngoingblah/watt-activation/part-130
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usesLearningRateDecayblah/watt-activation/part-133
true
showsHighPerplexityblah/watt-activation/part-133
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hasPersistentHighLossblah/watt-activation/part-133
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hasTotalStepsblah/watt-activation/part-133
16670
presupposes16670TotalStepsblah/watt-activation/part-133
16670
hasCripplingLogicIssuesblah/watt-activation/part-133
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totalStepsblah/watt-activation/part-136
16670
usesGradientDescentblah/watt-activation/part-136
null
includesTrainingStepblah/watt-activation/part-140
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hasTotalStepsblah/watt-activation/part-140
16670
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hasTotalTokensProcessedblah/watt-activation/part-140
54640640
hasElapsedTimeMinutesblah/watt-activation/part-140
75.9
hasPriorBestValidationPplblah/watt-activation/part-140
421.1
hasAverageTokensPerSecondblah/watt-activation/part-140
12001
usesCl100kTokenizerblah/watt-activation/part-140
cl100k
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nearingEarlyStageCompletionblah/watt-activation/part-150
null
usesLlamaStyleTokensblah/watt-activation/part-150
null
showsDecreasingLossTrendblah/watt-activation/part-150
null
reportedByblah/watt-activation/part-150
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hasStablePerformanceblah/watt-activation/part-150
null
hasTotalStepsblah/watt-activation/part-150
16684
inProgressblah/watt-activation/part-150
null
knownToHaveValidationblah/watt-activation/part-150
null
isOngoingblah/watt-activation/part-155
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showsDecreasingLossblah/watt-activation/part-155
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hasTotalStepsblah/watt-activation/part-155
16684
needsMoreTimeblah/watt-activation/part-169
{}
catchesUpOnTokensblah/watt-activation/part-169
{}
undergoesCosineDecayblah/watt-activation/part-169
{}
learnsSlowlyblah/watt-activation/part-169
{}
computesTokensSeenblah/watt-activation/part-169
~82M
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2
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{}
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8e-06
nearsCompletionblah/watt-activation/part-169
{}
producesCheckpointsblah/watt-activation/part-169
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hasTokensPerSecondblah/watt-activation/part-169
12000
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~33 min
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chugging
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~42 min
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true
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2789.1
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2732.6
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303s
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null
temporalOrderblah/watt-activation/part-230
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true
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6min
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4.5679
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10K
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References (99)

99 references
  1. [1]Part 1192 facts
    ctx:discord/blah/general/part-119
  2. [2]Part 371 fact
    ctx:discord/blah/random/part-37
  3. [3]Part 7210 facts
    ctx:discord/blah/safiersemantics/part-72
  4. [4]Part 172 facts
    ctx:discord/blah/training-and-evals/part-17
  5. [5]Part 342 facts
    ctx:discord/blah/training-and-evals/part-34
  6. [6]Part 671 fact
    ctx:discord/blah/unturf/part-67
  7. [7]Part 41 fact
    ctx:discord/blah/vidya/part-4
  8. [8]Part 37 facts
    ctx:discord/blah/vidya/part-3
  9. [9]Part 91 fact
    ctx:discord/blah/watt-activation/part-9
  10. [10]Part 2112 facts
    ctx:discord/blah/watt-activation/part-21
  11. [11]Part 3211 facts
    ctx:discord/blah/watt-activation/part-32
  12. [12]Part 391 fact
    ctx:discord/blah/watt-activation/part-39
  13. [13]Part 352 facts
    ctx:discord/blah/watt-activation/part-35
  14. [14]Part 441 fact
    ctx:discord/blah/watt-activation/part-44
  15. [15]Part 337 facts
    ctx:discord/blah/watt-activation/part-33
  16. [16]Part 581 fact
    ctx:discord/blah/watt-activation/part-58
  17. [17]Part 941 fact
    ctx:discord/blah/watt-activation/part-94
  18. [18]Part 9118 facts
    ctx:discord/blah/watt-activation/part-91
  19. [19]Part 981 fact
    ctx:discord/blah/watt-activation/part-98
  20. [20]Part 954 facts
    ctx:discord/blah/watt-activation/part-95
  21. [21]Part 1251 fact
    ctx:discord/blah/watt-activation/part-125
  22. [22]Part 1276 facts
    ctx:discord/blah/watt-activation/part-127
  23. [23]Part 1304 facts
    ctx:discord/blah/watt-activation/part-130
  24. [24]Part 1336 facts
    ctx:discord/blah/watt-activation/part-133
  25. [25]Part 1362 facts
    ctx:discord/blah/watt-activation/part-136
  26. [26]Part 14010 facts
    ctx:discord/blah/watt-activation/part-140
  27. [27]Part 1508 facts
    ctx:discord/blah/watt-activation/part-150
  28. [28]Part 1555 facts
    ctx:discord/blah/watt-activation/part-155
  29. [29]Part 16916 facts
    ctx:discord/blah/watt-activation/part-169
  30. [30]Part 2011 fact
    ctx:discord/blah/watt-activation/part-201
  31. [31]Part 2102 facts
    ctx:discord/blah/watt-activation/part-210
  32. [32]Part 2021 fact
    ctx:discord/blah/watt-activation/part-202
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      [2026-03-16 21:05] foxhop.: ● 23.6GB — that's tight on the 4090 (24GB). Batch 16 might OOM. Let me check with batch 8: ● Bash(python3 -c " n_embd=1536; n_layer=16; block_size=1024; total=467466240…) ⎿  batch= 4: 11.5 GB OK ba
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      [2026-03-20 11:25] foxhop.: awesome new video card with 12G & over 3k cuda cores! [2026-03-20 11:25] foxhop.: ? [2026-03-20 11:27] foxhop.: "We're building the disk." [2026-03-20 11:28] foxhop.: this screams GPT switch all "the" toward "a"
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      [2026-03-07 05:32] xenonfun: ``` Not good. The loss trajectory tells a clear story: ┌────────┬─────────────────────────┐ │ Iters │ Avg Loss │ ├────────┼─────────────────────────┤ │ 0-2K │ 6.56 (learning) │
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      [2026-03-07 21:54] xenonfun: ``` iter 8000/10000 | loss=4.2647 | PPL=71.1 | lr=6.16e-05 | 2.2 it/s (9.1K tok/s) | mem=1848MB peak=20665MB Saved checkpoint: ./akan_gpt2_checkpoints/checkpoint_iter_8000.npz iter 8500/10000 | loss=4.2438
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      [2026-03-08 00:46] xenonfun: ``` Looks good. Now let me calculate the exact iterations and launch: - 133M tokens / 4096 = 32,471 iters per epoch - 2 epochs = 64,942 total iters - Already done: 10,000 - Remaining: 54,942 iters (rou
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      [2026-03-09 04:03] xenonfun: ### What context count we do at this scale? ⏺ From the measurements we have, memory scales roughly linearly with total tokens in the batch: - BS=4, seq=1024 → 4,096 tokens → ~40 GB - BS=8, seq=1024 → 8,192
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      [2026-03-09 03:33] xenonfun: ❯ we want to do 2K seq tho ⏺ Doubling seq doubles the activation memory. BS=8, seq=2048 = same logit tensor size as BS=16, seq=1024 — which hit 85GB. We need to re-check BS. BS=4, seq=2048 = 8,192 tokens/bat
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      [2026-03-09 04:13] xenonfun: [resume] loading step_002000... resumed at step 2000, data_pos=16,392,000 [train] 16,670 steps | BS=4 SEQ=2048 | LR=1e-04 warmup=500 save every 2000 | val every 2000 | log every 100 checkpoint
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      [2026-03-09 18:10] xenonfun: ``` Prompt: 'The most important discovery in science was' temp=0.8 top_k=40 stop=<|endoftext|> (100257) [compiled] ──────────────────────────────────────────────────────────── The most important discovery in
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      [2026-03-09 16:27] xenonfun: ⏺ For batch prefill, each attention class's forward() currently runs _gated_cumsum over the full sequence and returns output — but throws away the final recurrent state. The step() method maintains that state
  83. [83]1653 facts
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      [2026-03-09 19:01] xenonfun: ``` Mode: qa temp=0.8 top_k=40 stop=<|endoftext|> (100257) [compiled] Instruction: 'What is photosynthesis?' ──────────────────────────────────────────────────────────── What is photosynthesis? The followin
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      [2026-03-10 03:42] xenonfun: ``` What the fix looks like: Coupling κ_g is a scalar per group. Its gradient through the sync step is tractable: at first order, Δcoupling_g ∝ -(∂loss/∂spectra_synced) · (mean_spec_g - spectra_g) — the reado
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      [2026-03-11 03:51] xenonfun: ```# coupling (K) and adjacency are structural constants — not updated. 598 + # v2: update harmonic_coeffs (G×H learned frequency weights) 599 + # v3: update mode_amplitudes (k scalars,
  86. [86]24217 facts
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      [2026-03-12 04:42] xenonfun: (files: Screenshot_2026-03-12_at_12.41.55_AM.png) [2026-03-12 04:49] xenonfun: `http://phase-pipeline.xenon.fun.local:8000/dashboard` it sets routes like this but if I refresh browser page those don't resolve b
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      [2026-03-12 07:06] xenonfun: ```[03:04:05] step 2000/12432 16.1% txt=4.411(82ppl) img=0.000 aud=2.025 r=0.375 lr=4.79e-05 150ms 69,028tok/s [T:1000 I:0 A:1000] eta=26min VAL step 2000 loss=4.4035 ppl=81.7 * best [03:04:29]
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      [2026-03-12 13:11] xenonfun: ✅ Phase 0 confirmed working — r_global rises monotonically from 0.07 → 0.96 across 16 steps on the production multimodal checkpoint. The architecture supports iterative generation. This is the green light to p
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      [2026-03-13 05:30] xenonfun: ``` I wrote the full plan in docs/claude/plans/tokenizerless_phase_stream_plan.md. Core recommendation from the plan: - do not do pure one-byte-per-step modeling first - build a tokenizerless byte_patch
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      [2026-03-17 06:32] xenonfun: ``` 44 +├── antenna.py # AntennaHarmonicBlock + AntennaLM: field-mediated byte LM 45 +├── antenna_probes.py # Diagnostic probes: impulse, memory, coupling, leakage, boundary 46 +├── an
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      [2026-03-18 17:41] xenonfun: ``` ❯ how expensive are probes? ⏺ Let me check what the probes actually do at the --probe-every 2000 interval. ⏺ Searched for 1 pattern (ctrl+o to expand) ⏺ At --probe-every 2000, each probe step runs: 1.
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      [2026-03-18 17:29] xenonfun: ⏺ Here's the status: Implementation complete and pushed: - AnchorBind module in harmonic_mlx/antenna.py — 32 soft anchors on S^{d_bind-1}, softmax assignment, residual fusion - Wired into AntennaHarmonicB
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      [2026-03-18 19:30] xenonfun: ``` checkpoint dir: checkpoints/ham_G16_20K ──────────────────────────────────────────────────────────────────────── step 200/20000 1.0% BPB=4.149 r=0.228 SNR=-12.7dB C=0.7b lr=9.95e-05 80,154tok/s
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      [2026-03-19 04:31] xenonfun: ``` Mode: byte-level temp=0.7 max_tokens=300 Prompt: 'The quick brown fox ' ──────────────────────────────────────────────────────────── The quick brown fox ris pis se te at ti odinrbar 0bouone
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      [2026-03-21 23:19] xenonfun: ``` === BPE-8K: cache growth 200→2000 === Loaded 20480128 bytes from /Users/ms/MS/HarmonicMLX/data/fineweb_edu_bpe8k.npy KickModel ANALYTICAL training: 30000 steps, seq_len=128, lr=0.0005, momentum=0.9
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      [2026-04-19 09:46] xenonfun: loaded 24999946 bytes from /Users/ms/MS/HarmonicRust/data/curriculum/domain_tinystories.bin step 0 loss=6.1092 bpb=8.814 gnorm=10.6885 lr=4.00e-6 9259 tok/s step 50 loss=2.8955 bpb=4.177 gnorm=2.2132
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      [2026-04-20 00:14] xenonfun: ``` ⏺ Run complete. Task #5 done. Final head-to-head: ┌────────────┬────────────┬─────────────────────────────┐ │ │ V1 rotadam │ V2 fixed │ ├────────────┼────────────┼────
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      [2026-04-23 19:13] xenonfun: ``` Register match: partial. - ✅ tinystories/narrative show real conditioning — "little bear", "mommy", "kitchen", "store", "pigs", simple-declarative register. Recognizable. - ❌ edu/science/dense_science/
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      [2026-05-01 02:47] xenonfun: It wants 150M or so so think the chatgpt-2 in 24hr is looking achievable. we do need to get more dataset here. [2026-05-01 02:50] lisamegawatts: mines downloading datasets and parsing now, added a 4096 option [2

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