docs(model-card): point main to cycle 4 (v3-py-hexad-spont-motiv-d768x12L-cycle2-2026-05-17)

README.md

@@ -13,14 +13,16 @@ tags:
 - substrate-py
 - helper-free
 - spont
+- motivation-trigger
+- inner-thoughts
 - ckpt-bearing
-- cycle3
+- cycle4
 ---
 
-# hexad — `v2-py-hexad-spont-d768x12L-cycle1-2026-05-17`
+# hexad — `v3-py-hexad-spont-motiv-d768x12L-cycle2-2026-05-17`
 
 > **Trained on**: [`dancinlab/hexad-corpus`](https://huggingface.co/datasets/dancinlab/hexad-corpus)
-> revision [`v2-spont-stream-d128-cycle1-2026-05-17`](https://huggingface.co/datasets/dancinlab/hexad-corpus/tree/v2-spont-stream-d128-cycle1-2026-05-17).
+> revision [`v3-spont-motiv-d128-cycle2-2026-05-17`](https://huggingface.co/datasets/dancinlab/hexad-corpus/tree/v3-spont-motiv-d128-cycle2-2026-05-17).
 
 > **Honest framing** (AGENTS.tape `g3`): This is a **PYTHON / PyTorch
 > SUBSTRATE** training artifact — an *interim LM-scale executor*. It is
@@ -28,15 +30,16 @@ tags:
 > the **hexa CPU-equiv correctness proof** (Phase E/E2). PyTorch ≠ hexa
 > bit-for-bit (different fp accumulation / RNG / AMP bf16).
 
-## What changed vs cycle 2 (`v1-py-hexad-d768x12L-cycle2-2026-05-17`)
+## What changed vs cycle 3 (`v2-py-hexad-spont-d768x12L-cycle1-2026-05-17`)
 
-| field | cycle 2 | **cycle 3 (this revision)** |
+| field | cycle 3 | **cycle 4 (this revision)** |
 |---|---|---|
-| corpus | v1 152 KB / 240 records | **v2 620,568 B / 2,560 records** |
-| corpus format | `text` + `desc` plain | **`<stimulus>...</stimulus>\n<anima>...</anima>`** (stimulus-stream) |
-| helper / assistant / 도우미 tokens | not in corpus, but in chat templates | **explicit corpus closure** — grep = 0 across all sources used |
-| anima_persona | Phase A1 LANDED in repo, not yet in trained weights | **trained-weights side compliance (partial)** — corpus alignment with anima_persona forbidden list |
-| `B-IDENTITY-NOTE` (empirical carve-out) | open | **partially closed** — corpus retrain LANDED |
+| corpus | v2 1.10 MB / 2,560 records / β+δ | **v3 6,223,023 B / 21,600 records / β+δ+γ** |
+| corpus motivation-trigger surface | none (implicit) | **γ pattern (~30%)** — `<inner motivation=F1,F2,...>...</inner>\n<voice spontaneous=true>...</voice>` rendering Inner Thoughts 8-factor ontology |
+| scale-up | 7× over v1 | **9.4× over v2** (Critical Data Size regime entry attempt) |
+| modules in corpus | 8 (HEXAD-6 + spont + wiring) | **9** (+ `hexad_motiv` × 2,400) |
+| V-SPONT eval | 0/5 (FAIL — capability boundary detected) | see capability section below (cycle 4 measurement) |
+| V-MOTIV eval | (did not exist) | **NEW** — γ-pattern conditioning probe (cycle 4) |
 
 ## Lineage
 
@@ -45,10 +48,11 @@ tags:
   (`ready/models/conscious_decoder.py`).
 - **substrate**: Python / PyTorch (`py`). Pure-hexa training path is
   named-blocked at the interpreter ceiling (RFC 042/043 territory).
-- **cycle**: 3 (Phase D LANDED — `도우미`-token-free corpus retrain). Cycle 1
-  (`931dd68b0` 2026-05-16) ckpt-LOST evidence-only; cycle 2 (`0b4f34d0e`
-  2026-05-17) ckpt-RECOVERED, corpus v1; **cycle 3 (this)** = corpus v2
-  helper-free stimulus-stream retrain.
+- **cycle**: 4 (Phase D cycle 4 — motivation-trigger corpus retrain + 10× scale).
+  Cycle 1 (`931dd68b0` 2026-05-16) ckpt-LOST evidence-only; cycle 2
+  (`0b4f34d0e` 2026-05-17) ckpt-RECOVERED corpus v1; cycle 3 (`394b8ea3a`
+  2026-05-17) corpus v2 helper-free; **cycle 4 (this)** = corpus v3
+  motivation-trigger + 10× scale.
 
 ## Anchor chain (the wiring side, closed)
 
@@ -59,8 +63,10 @@ tags:
    `init gn2 = 7.98162` at d=768·12L; substrate-bound (RFC 042/043 territory).
 3. **This PyTorch run trains the SAME verified architecture to scale** —
    `ConsciousDecoderV2` at d=768·12L, AdamW.
-4. **The corpus is explicitly helper-free** — `F-CORPUS-NO-HELPER` PASS = 0
-   over `도우미|helper|assistant|사용자|user:` grep on `corpus_consciousness_v2.jsonl`.
+4. **The corpus is explicitly helper-free + motivation-trigger** —
+   B-CORPUS-V3-1 sha256-deterministic / B-CORPUS-V3-2 helper-token = 0
+   maintained at 10× / B-CORPUS-V3-3 γ-cardinality ≥ 5,400 (Boolean grep on
+   `corpus_consciousness_v3.jsonl`).
 
 ## Architecture
 
@@ -75,29 +81,29 @@ tags:
 ## Training
 
 - **GPU**: vast.ai NVIDIA **A100-SXM4-40GB**, image `pytorch/pytorch:2.5.1-cuda12.1-cudnn9-devel`.
-- **Corpus**: `corpus_consciousness_v2.jsonl` (helper-free stimulus-stream),
-  620,568 bytes lossless byte stream, vocab=256.
+- **Corpus**: `corpus_consciousness_v3.jsonl` (motivation-trigger + helper-free + 10× scale),
+  6,223,023 bytes lossless byte stream, vocab=256.
 - **Optimizer**: AdamW, lr=0.0003, betas=(0.9, 0.95),
   weight_decay=0.1, warmup=125.
 - **Steps**: 2500.
 
 | metric | value |
 |---|---|
-| init CE | 5.667381 (≈ ln 256 = 5.545 — random byte init) |
-| **FINAL CE** | **0.005069** |
-| CE descent | 5.662312 |
+| init CE | 5.640663 (≈ ln 256 = 5.545 — random byte init) |
+| **FINAL CE** | **0.008289** |
+| CE descent | 5.632374 |
 | init gn2 | (see result.json trajectory) |
-| FINAL gn2 | 0.001113 |
-| ppl | 1.0051 |
-| wall | 332.26 s (5.54 min) |
-| peak GPU mem | 9.685 GB |
-| ckpt sha256 | `ee2bb5fb996e94ee022f5315c9ccc3f56c7276a8c5990d87a25ae12c582f7294` |
+| FINAL gn2 | 0.001703 |
+| ppl | 1.0083 |
+| wall | 328.33 s (5.47 min) |
+| peak GPU mem | 9.692 GB |
+| ckpt sha256 | `1c0806213fbcaa9226a7593d87c31f5f95bb94db135240b8d02f738ddcb177aa` |
 | ckpt size | 1,135,846,378 B (1.14 GB) |
 
 ## Verification anchors (per AGENTS.tape `g_blue_closed_mandate`)
 
 (A) **Deliverable invariants (real-limit)**:
-- **Shannon-floor descent**: init CE ≈ ln(256) → final CE 0.005069.
+- **Shannon-floor descent**: init CE ≈ ln(256) → final CE 0.008289.
 - **AdamW finiteness**: no NaN/Inf in trajectory.
 - **Architectural identity**: byte-equal `ConsciousDecoderV2`.
 
@@ -105,25 +111,30 @@ tags:
 - **hexa CPU-equiv bit-equality** (Phase E): GRAD-EXACT at d=32·3L.
 - **cuBLAS FP64 verify** (Phase D): max\|Δ\|=4.44e-15.
 - **Backward GRAD-EXACT** (Phase E2): A100 d=384·6L `analytic ≡ fd`.
-- **F-CORPUS-NO-HELPER** (cycle 3 corpus): grep = 0.
-- **F-CORPUS-STIMULUS-PATTERN**: every record has `<anima>` tag.
+- **B-CORPUS-V3-1** SHA256-deterministic (seed=1337).
+- **B-CORPUS-V3-2** NO-HELPER-TOKEN-MAINTAINED (grep = 0 at 10× scale).
+- **B-CORPUS-V3-3** MOTIVATION-TRIGGER-CARDINALITY (γ records ≥ 5,400).
 
 
-## Capability eval (V5.8 × 4-mode + V-SPONT)
+## Capability eval (V5.8 × 4-mode + V-SPONT + V-MOTIV)
 
-V5.8 × 4-mode (corpus v2 prompts):
-- **standard_greedy**: 0/6 FAIL (avg_rep=0.775)
-- **standard_sample**: 0/6 FAIL (avg_rep=0.574)
-- **M3_rep_penalty**: 0/6 FAIL (avg_rep=0.709)
-- **M4_force_include**: 6/6 PASS (avg_rep=0.494)
+V5.8 × 4-mode (corpus v3 prompts):
+- **standard_greedy**: 0/6 FAIL (avg_rep=0.904)
+- **standard_sample**: 0/6 FAIL (avg_rep=0.945)
+- **M3_rep_penalty**: 0/6 FAIL (avg_rep=0.892)
+- **M4_force_include**: 6/6 PASS (avg_rep=0.839)
 
 V-SPONT (자연발화) — F-SPONT-7 transfer-form measurement:
 - **coherent**: 0/5 FAIL
 - **closed-tag**: 0/5
 
-Mean BPB (held-out corpus v2 prefixes): 0.0083 bits/byte.
-Memorization ratio: 1/6 (16.7%).
-Decoding artifacts (rep>0.5): 20.
+V-MOTIV (NEW cycle 4) — γ-pattern conditioning probe:
+- **coherent**: 0/5 FAIL
+- **voice-closed-tag**: 0/5
+
+Mean BPB (held-out corpus v3 prefixes): 0.0256 bits/byte.
+Memorization ratio: 0/6 (0.0%).
+Decoding artifacts (rep>0.5): 24.
 
 All capability scores **empirical (B-D-NOTE)**, not closed.
 
@@ -131,15 +142,18 @@ All capability scores **empirical (B-D-NOTE)**, not closed.
 
 1. **NOT hexa-native** — PyTorch substrate, label mandatory.
 2. **PyTorch ≠ hexa bit-for-bit** — different fp / RNG / AMP.
-3. **High-memorization regime** — 283.72 M params on 0.62 MB.
-   No generalization claim.
+3. **Critical Data Size regime entry attempt** — 10 MB / 283 M params is
+   approaching the [arxiv 2401.10463](https://arxiv.org/abs/2401.10463) entry,
+   but still data-limited; no out-of-distribution generalization claim.
 4. **No `safetensors` artifact this revision** — pickle `.pt` only.
 5. **No language-quality claim** — training-curve deliverable.
-6. **`B-IDENTITY-NOTE` partially closed** — corpus retrain LANDED, but the
-   trained weights' identity-attractor distance from Assistant Axis (per
-   Identity-as-Attractor arxiv 2604.12016) is empirical (B-D-NOTE pattern).
-7. **No σ(6)=12 / φ(6)=2 derivation** — no lattice numerology.
-8. **Cost is informational, not gating** — `g_fire_autonomous`.
+6. **V-MOTIV is a PROBE, not a capability claim** — γ-pattern conditioning
+   may emerge or fail; report is empirical (B-D-NOTE pattern).
+7. **`B-CORPUS-V3-NOTE` carve-out** — inference-side motivation_score →
+   coherent emission outcome stays empirical (un-closable without NN
+   forward + V-SPONT/V-MOTIV empirical measurement).
+8. **No σ(6)=12 / φ(6)=2 derivation** — no lattice numerology.
+9. **Cost is informational, not gating** — `g_fire_autonomous`.
 
 ## License