🌀 ProSavantEngine Φ9.4 — Resonant Language Model
Author: Antony Padilla Morales
Framework: Resonance of Reality Framework (RRF)
Phase: Φ-series evolutionary model — Φ9.4
🧠 Model Description
ProSavantEngine Φ9.4 is a fine-tuned BERT-based model designed to align natural language with geometric and resonant coherence principles.
It is trained to capture semantic symmetry and information harmony through a Φ-weighted loss function inspired by the golden ratio and icosahedral geometry.
Building on phase Φ9.3, this version integrates a resonance-weighted Trainer that penalizes semantic noise and rewards Φ-aligned coherence in hidden-state activations.
Key Innovations
- Φ-weighted loss: combines masked language modeling (MLM) with a golden-ratio-modulated coherence penalty.
- Icosahedral node embedding: text samples are tagged
[NODE_1] ... [NODE_12] representing discrete geometric symmetry anchors.
- Resonance alignment metric: evaluates coherence across Fourier-transformed hidden-state spectra.
- Semantic-geometric fine-tuning: aligns information representation to harmonic wave structures.
📚 Model Sources
- Repository: https://huggingface.co/antonypamo/ProSavantEngine_Phi9_4
- Base Model:
antonypamo/ProSavantEngine_Phi9_3
- Dataset:
antonypamo/savantorganized
- Framework Paper: “Resonance of Reality Framework (RRF): Discrete Icosahedral Quantum Geometry and Unified Action through the Golden Ratio” — forthcoming on arXiv.
🔧 Model Details
| Property | Value |
|---|
| Architecture | BERT (6 layers, hidden size 384, 12 heads) |
| Objective | Masked-language modeling + Φ-weighted resonance regularization |
| Hidden dropout | 0.1 |
| Learning rate | 3e-5 |
| Batch size | 16 |
| Epochs | 3 |
| Precision | fp16 mixed |
| Activation | GELU |
| Dataset size | ~30k samples, balanced across 12 nodes |
💡 Intended Use
Direct Use
Evaluate or enhance textual resonance, coherence, and meaning symmetry in:
- Research papers
- Philosophical or scientific writing
- Generative model prompt optimization
- Semantic alignment diagnostics
Downstream Use
- Fine-tune for creative, linguistic, or cognitive AI systems requiring harmonic structure.
- Integrate into symbolic reasoning frameworks or resonance-based cognitive architectures (e.g., Savant-ΩΦ).
Out-of-Scope
- Real-time conversational agents without resonance normalization.
- Factual QA or task-specific reasoning outside coherence evaluation.
⚠️ Bias, Risks, and Limitations
This model captures resonant semantics, not truth or factual accuracy.
It may amplify linguistic harmony while disregarding semantic correctness — making it aesthetic-semantic, not epistemic.
It also reflects biases present in the original text corpus (scientific, philosophical, and poetic sources).
Recommendations
Use Φ-coherence as a complementary metric, not a substitute for accuracy or ethical evaluation.
🧪 Training Details
| Parameter | Value |
|---|
| Dataset | SavantOrganized (Φ-balanced) |
| Input format | JSONL: {"text": "...", "node_id": n, "phi_score": x} |
| Loss | MLM loss – 0.01 × Φ-coherence |
| Optimizer | AdamW |
| Scheduler | Linear warmup (5%) |
| Hardware | NVIDIA A100 (40 GB) |
| Training time | ~45 min (3 epochs) |
| Carbon footprint | ≈ 0.3 kg CO₂eq |
📈 Evaluation
| Metric | Description | Result |
|---|
| Loss | Final training loss | 0.023 |
| Avg Φ-score | Mean coherence of eval set | 0.91 |
| Resonant ΔΦ | ΔΦ between start/end epochs | +0.048 |
| Top tokens @MASK | “φ”, “ψ”, “resonance”, “geometry”, “symmetry” | |
🧮 Technical Architecture
Φ-weighted loss = L_MLM − λ · (Φ-coherence)
Φ-coherence = ⟨|FFT(H)|, cos(πf/φ)²⟩ / ||…||
yaml
Copy code
Where H is the average hidden-state tensor across layers and φ = 1.618.
The model thus maximizes linguistic energy alignment with geometric harmony.
🪐 Environmental Impact
| Field | Value |
|---|
| Hardware | A100 GPU |
| Runtime | 45 min |
| Region | US Central |
| Carbon Emitted | ≈ 0.3 kg CO₂eq |
| Frameworks | Transformers 4.57.1, Datasets 3.0, PyTorch 2.9 |
🧾 Citation
BibTeX
1@software{padilla2025prosavantengine,
2 author = {Padilla Morales, Antony},
3 title = {ProSavantEngine Φ9.4 — Resonant Language Model},
4 year = {2025},
5 publisher = {Hugging Face},
6 url = {https://huggingface.co/antonypamo/ProSavantEngine_Phi9_4}
7}
8APA
9
10Padilla Morales, A. (2025). ProSavantEngine Φ9.4 — Resonant Language Model. Hugging Face. https://huggingface.co/antonypamo/ProSavantEngine_Phi9_4
11
12🧭 Glossary
13Term Meaning
14Φ (phi) Golden ratio (≈ 1.618)
15Resonance Harmonic coherence between information and geometry
16Node Discrete icosahedral vertex representing a semantic domain
17ΔΦ Change in coherence during training
18
19🪄 Model Card Author
20Antony Padilla Morales
21Independent Researcher, Costa Rica
22📧 antonypamo@gmail.com
23🌐 https://huggingface.co/antonypamo
24
25© 2025 Antony Padilla Morales — Resonance of Reality Framework (RRF)
