Training Dynamics
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Training Dynamics has 11 facts recorded in Dontopedia across 10 references.
Mostly:are readable at glance by2d chart(1), follows(1), teleologically builds coherence(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (10)
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.
affectsTrainingAffects Training(1)
- Initialization Method
ex:initialization-method
bottleneckInPriorBottleneck in Prior(1)
- Optimizer Geometry
ex:optimizer-geometry
changesChanges(1)
- Packing
ex:packing
enablesDiverseModeUsageEnables Diverse Mode Usage(1)
- Bpsk Rotor
ex:bpsk-rotor
enablesHighBandwidthEnables High Bandwidth(1)
- Bpsk Rotor
ex:bpsk-rotor
enablesLowREnables Low R(1)
- Bpsk Rotor
ex:bpsk-rotor
followsFollows(1)
- Final Perplexity
ex:final-perplexity
hasMemberHas Member(1)
- Causal Narrative
ex:causal-narrative
isHealthiestSeenIs Healthiest Seen(1)
- Current Training Dynamics
ex:current-training-dynamics
isHealthyIs Healthy(1)
- Resonantwirelm
ex:resonantwirelm
Other facts (10)
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.
| Predicate | Value | Ref |
|---|---|---|
| Are Readable at Glance By2d Chart | true | [1] |
| Follows | Phase Synchronization Regime | [2] |
| Teleologically Builds Coherence | Lohe Sync | [3] |
| Altered by Packing | true | [4] |
| Prioritizes Specialization Over Sync | true | [5] |
| Are Self Regulating Over Time | progressively | [6] |
| Requires Stop Signalling | Active Layer Dynamics | [7] |
| Described As | healthiest ... we've seen | [8] |
| Descent Behavior | Late Cosine Descent Flattened | [9] |
| Rdf:type | Training Property | [10] |
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.
References (10)
ctx:discord/blah/training-and-evals/part-25ctx:discord/blah/watt-activation/part-55ctx:discord/blah/watt-activation/part-204ctx:discord/blah/watt-activation/part-250ctx:discord/blah/watt-activation/part-267ctx:discord/blah/watt-activation/part-425ctx:discord/blah/watt-activation/part-696ctx:discord/blah/watt-activation/394- full textwatt-activation-394text/plain2 KB
doc:agent/watt-activation-394/027ab2ca-0cf4-4693-ba6c-1f9208e93d86Show excerpt
[2026-03-19 03:59] xenonfun: ⏺ Look at those diagnostics: - r = 0.21 — beautifully low coherence, no over-sync. The BPSK encoding with 8 groups keeps things differentiated. - SNR = -13.4dB — deep in the noise regime, lots of room to bu…
ctx:discord/blah/watt-activation/686- full textwatt-activation-686text/plain3 KB
doc:agent/watt-activation-686/87dc1f6d-de3b-4f99-bdf2-bfce9ede6dd6Show excerpt
[2026-04-24 00:49] xenonfun: have cliffordnet workong on the medical images, does that at 60% but only 9K parms, but CNNs are in the 80s. its really not good at simple stuff does suggest hybrid of our manifoldunit which is great at simple b…
ctx:claims/beam/1a9575d4-0f05-41b2-a8bf-3a9f1dd9dcb9- full textbeam-chunktext/plain1 KB
doc:beam/1a9575d4-0f05-41b2-a8bf-3a9f1dd9dcb9Show excerpt
- **Description**: Coefficient for L2 norm of the weights. - **Range**: Typically between \(10^{-6}\) and \(10^{-2}\). - **Example Values**: \(1e-6\), \(1e-5\), \(1e-4\), \(1e-3\), \(1e-2\). - **Dropout Rate** - **De…
See also
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