order parameter
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)
order parameter has 23 facts recorded in Dontopedia across 10 references, with 4 live disagreements.
Mostly:rdf:type(4), moves toward exponentially(2), measures(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (7)
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.
includesIncludes(2)
- Jsonl Output Per Step Diagnostics
ex:jsonl-output-per-step-diagnostics - Logged Per Step System
ex:logged-per-step-system
appliesToApplies to(1)
- Patch 1
ex:patch-1
includesRGlobalAsIncludes R Global As(1)
- Last Metrics
ex:last-metrics
indicatedByIndicated by(1)
- Synchronization
ex:synchronization
isIs(1)
- R Cross
ex:r-cross
populatesWithPopulates With(1)
- Layer 1 Side Channel
ex:layer-1-side-channel
Other facts (22)
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 |
|---|---|---|
| Rdf:type | Model Parameter | [6] |
| Rdf:type | Metric | [8] |
| Rdf:type | Learning Rate Signal | [9] |
| Rdf:type | Metric | [10] |
| Moves Toward Exponentially | 0 Disorder | [1] |
| Moves Toward Exponentially | 1 Perfect Alignment | [1] |
| Measures | Degree of Synchronization | [1] |
| Measures | Degree of Synchronization | [7] |
| Moves Toward | 1 | [7] |
| Moves Toward | 0 | [7] |
| Moves Condition Dependent on | Attractive Coupling | [7] |
| Moves Condition Dependent on | Repulsive Coupling | [7] |
| Signals Lr Adjustment | true | [2] |
| Serves As | Learning Rate Signal | [2] |
| Increases From to | 0.45 → 0.88 | [3] |
| Decreases With Resolution | null | [4] |
| Indicates No Full Sync | Burst Region | [5] |
| Has Value R | 0.888 | [5] |
| Moves Toward Speed | exponential | [7] |
| Source Variable | r_global | [8] |
| Mapped to | learning rate signal | [9] |
| Part of | System Data | [10] |
Timeline
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References (10)
ctx:discord/blah/watt-activation/part-185ctx:discord/blah/watt-activation/part-390ctx:discord/blah/watt-activation/part-533ctx:discord/blah/watt-activation/part-565ctx:discord/blah/watt-activation/part-538ctx:discord/blah/watt-activation/139- full textwatt-activation-139text/plain2 KB
doc:agent/watt-activation-139/84b665a8-03e4-433b-97dc-f40068180b02Show excerpt
[2026-03-09 07:23] xenonfun: ⏺ Training is resumed from step 10000. The NaN is fixed — all three patches held: 1. r_global = mx.sqrt(sum_sq + 1e-8) — eps inside sqrt for order parameter 2. mean_spec / mx.sqrt(sum_sq + 1e-8) — eps insid…
ctx:discord/blah/watt-activation/185- full textwatt-activation-185text/plain3 KB
doc:agent/watt-activation-185/fcee3d0e-68fc-4f0b-ad9d-157115bfbadeShow excerpt
[2026-03-10 02:38] lisamegawatts: i think this part is wrong, it should not init at zero they need frequencies. i also don't think it needs gelu, the linear error is inherently in the sphere; The Lohe sphere model, a generalization of the K…
ctx:discord/blah/watt-activation/183- full textwatt-activation-183text/plain3 KB
doc:agent/watt-activation-183/aa64c83c-e728-416e-9b09-62cb1782add2Show excerpt
[2026-03-10 02:09] xenonfun: ``` Key findings: 1. RotationalAdamW: strong convergence from scratch (9.9→7.6 train loss), consistent 11.6K tok/s — expected baseline for cl100k vocab (lower than BPE-8K benchmark's 22K due to 100K-class l…
ctx:discord/blah/watt-activation/388- full textwatt-activation-388text/plain2 KB
doc:agent/watt-activation-388/46a6b190-3823-4de5-b207-66c8e6b2684bShow excerpt
[2026-03-19 02:30] xenonfun: (files: Screenshot_2026-03-18_at_10.30.23_PM.png) [2026-03-19 02:30] lisamegawatts: ah you need to go adamw possible [2026-03-19 02:31] lisamegawatts: no rotation [2026-03-19 02:32] xenonfun: we got too synced …
ctx:discord/blah/watt-activation/488- full textwatt-activation-488text/plain3 KB
doc:agent/watt-activation-488/3b1655f5-5846-4949-99fa-94517d956b67Show excerpt
[2026-03-22 04:58] xenonfun: ⏺ 12.8K tok/s! Up from 8.6K with cached norms alone. The NEON SIMD dot_slice with vfmaq_f32 (fused multiply-add on 4 floats) gives another 49% speedup. Total speedup from the original 5.7K: ``` ┌───────────…
See also
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