Dontopedia

Training BPB

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

Training BPB has 20 facts recorded in Dontopedia across 3 references.

20 facts·18 predicates·3 sources

Mostly:is noisy per step(1), at do re mi cursor(1), on current stochastic batch(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (1)

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increasesValueOfIncreases Value of(1)

Other facts (18)

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.

18 facts
PredicateValueRef
Is Noisy Per Steptrue[1]
At Do Re Mi Cursortrue[1]
On Current Stochastic Batchtrue[1]
Is Do Re Mi Reweightedtrue[1]
Differs From Held Out Bpbtrue[1]
Statusdropping[2]
Has Value at Epoch{"epoch":10,"value":1.94}[2]
Rdf:typeMetric[3]
Weighting MethodDoReMi-reweighted[3]
Has Value2.78[3]
Based on LogTraining Log[3]
Loss Weighted by9 Domain Mix[3]
Measurement Scopecurrent stochastic batch[3]
Cursor MethodDoReMi cursor[3]
Noise Levelnoisy per-step[3]
Appearancescary[3]
ClassificationDoReMi bookkeeping artifact[3]
Is Regressionfalse[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.

isNoisyPerStepblah/watt-activation/part-686
true
atDoReMiCursorblah/watt-activation/part-686
true
onCurrentStochasticBatchblah/watt-activation/part-686
true
isDoReMiReweightedblah/watt-activation/part-686
true
differsFromHeldOutBpbblah/watt-activation/part-686
true
labelblah/watt-activation/345
Training BPB
statusblah/watt-activation/345
dropping
hasValueAtEpochblah/watt-activation/345
{"epoch":10,"value":1.94}
typeblah/watt-activation/683
ex:Metric
labelblah/watt-activation/683
Training BPB
weightingMethodblah/watt-activation/683
DoReMi-reweighted
hasValueblah/watt-activation/683
2.78
basedOnLogblah/watt-activation/683
ex:training-log
lossWeightedByblah/watt-activation/683
ex:9-domain-mix
measurementScopeblah/watt-activation/683
current stochastic batch
cursorMethodblah/watt-activation/683
DoReMi cursor
noiseLevelblah/watt-activation/683
noisy per-step
appearanceblah/watt-activation/683
scary
classificationblah/watt-activation/683
DoReMi bookkeeping artifact
isRegressionblah/watt-activation/683
false

References (3)

3 references
  1. [1]Part 6865 facts
    ctx:discord/blah/watt-activation/part-686
  2. [2]3453 facts
    ctx:discord/blah/watt-activation/345
    • full textwatt-activation-345
      text/plain3 KBdoc:agent/watt-activation-345/c59946eb-7ad9-465b-939c-f70436033800
      Show excerpt
      [2026-03-16 01:39] xenonfun: ⏺ Yes — principled noise injection is exactly what communications systems do. Three reasons it could help: 1. Stochastic resonance. In nonlinear systems (which Lohe sync IS), a small amount of noise can actua
  3. [3]68312 facts
    ctx:discord/blah/watt-activation/683
    • full textwatt-activation-683
      text/plain3 KBdoc:agent/watt-activation-683/1d89c3e1-d173-4432-968b-898b740f9ed3
      Show excerpt
      [2026-04-23 17:37] xenonfun: All 20 layers healthy — no issues. - Zero dead layers. Contribution ratio range: 34-157% (dead threshold is <1%). L0 dominates (157%) as expected input-conditioner; L1-L19 all 34-94%. - No gate collapse. α

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