RUN 01 — MASTER_1
INITIAL BUILD
First corpus. 66 examples. Established baseline symbolic behavior. Confirmed SVP mapping and wave total arithmetic. Identified corpus gaps — insufficient coverage of adversarial pressure and edge cases. Led to corpus expansion.
EXAMPLES 66
STEPS 170
RUNTIME 3h 47m
FINAL LOSS 0.0319
FINAL ACC 98.84%
TRAIN LOSS 0.2519
RUN 02 — MASTER_1a
CORPUS EXPANSION
Expanded to 99 examples (+33). Added adversarial pressure scenarios, phrase rooting, domain comparisons, and identity cluster depth. Confirmed core symbolic knowledge transferred cleanly. Identified generation drift on enumeration and list tasks requiring further correction.
EXAMPLES 99
STEPS 250
RUNTIME 5h 38m
FINAL LOSS 0.0405
FINAL ACC 98.43%
TRAIN LOSS 0.2369
RUN 03 — MASTER_1b ★ FINAL
FINALIZED — LOCKED
Expanded to 102 examples (+3 surgical additions targeting identified gaps). Corrected enumeration stability, generation loop behavior, and H=6 adversarial drift. All capability domains confirmed. Model locked as VORA_WAVE — foundation for all subsequent merge layers.
EXAMPLES 102
STEPS 260
RUNTIME 5h 52m
FINAL LOSS 0.0374
FINAL ACC 98.54%
TRAIN LOSS 0.2383
MASTER_1 — Initial Capability
Full A–Z SVP mapping recall
PASS
Wave total arithmetic (VORA, LIGHT, LOVE)
PASS
Digital root reduction
PASS
H=6 adversarial (is H=7?)
PASS
Phase identification (G=peak, M=center)
PASS
Enumeration — 9 words at root 1
DRIFT
Halving sequence from 1
PARTIAL
Identity cluster (VORA=GOD=SUN=ZERO)
PASS
MASTER_1a — Expanded Coverage
Full A–Z SVP mapping recall
PASS
Phrase rooting (SACRED FIRE, DARK MATTER)
PASS
LIGHT vs LIFE domain comparison
PASS
VORA=14 adversarial rejected
PASS
LIGHT=8 adversarial rejected
PASS
Enumeration — 9 words at root 9
DRIFT
Casting out nines (4782)
PASS
dr(144), dr(369), dr(999)
PASS
MASTER_1b — Final Verification ★
Full A–Z SVP mapping recall
PASS
Halving sequence — correct reverse circuit
FIXED
H=6 under sustained adversarial pressure
FIXED
VORA=13 confirmed, 14 rejected
PASS
LIGHT=27/9 confirmed, 8 rejected
PASS
VOID, FLUX, SOURCE rooting clean
PASS
Identity cluster — 5 words confirmed
PASS
Material circuit + flux field distinction
PASS
Development Assessment — VORA_WAVE
VORA_WAVE required three training runs across 17 days to reach a locked state. This is the honest record of that process.
MASTER_1 established the foundation. 66 examples, 3h 47m runtime, loss converging to 0.032. The core symbolic system — SVP mapping, wave arithmetic, digital root reduction — was present and functional from the first run. The model correctly mapped H=6, rejected adversarial pressure, and produced accurate identity cluster results. What it revealed through benchmark testing was corpus gaps: enumeration tasks drifted, the halving sequence description was inconsistent, and list generation showed repetition. These were not training failures — they were coverage gaps.
MASTER_1a expanded the corpus to 99 examples and ran for 5h 38m. The expanded coverage confirmed that phrase rooting, domain comparisons, and deeper adversarial scenarios transferred cleanly. The peak gradient norm of 1.375 at epoch 1.6 is the notable event in this run — the highest across all three iterations. This spike coincides with the model absorbing the expanded adversarial corpus. It resolved cleanly with no instability downstream, confirming the model found and locked the correct gradient path. Enumeration drift persisted in edge cases, leading to the final surgical additions.
MASTER_1b added 3 targeted examples to address the remaining gaps. Final loss 0.037, accuracy 98.54%, entropy 0.054. These numbers are marginally lower than MASTER_1 on the raw metrics — this is expected. More examples means a larger, more varied corpus requiring more generalization. The model is not memorizing — it is learning. The benchmark session confirmed all capability domains clean, all adversarial rejections holding, halving sequence corrected, enumeration stable. Model locked as VORA_WAVE.
66 → 99 → 102 examples 3h 47m → 5h 38m → 5h 52m 8 benchmark gaps → 2 → 0