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README.md
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| 1 |
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---
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language: en
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license: apache-2.0
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datasets:
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- antonypamo/savantorganized
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tags:
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- quantum-resonance
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- icosahedral-geometry
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- fine-tuning
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- bert
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- masked-language-modeling
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- resonance-of-reality-framework
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- savantengine
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- phi-series
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model-index:
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- name: ProSavantEngine Φ9.4
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results:
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- task:
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type: masked-language-modeling
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name: Φ-weighted Resonance Prediction
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dataset:
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name: SavantOrganized Φ-balanced corpus
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type: antonypamo/savantorganized
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metrics:
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- name: Training loss
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type: loss
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value: 0.023
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- name: Average Φ-coherence
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type: custom
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value: 0.91
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---
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# 🌀 ProSavantEngine Φ9.4 — Resonant Language Model
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**Author:** [Antony Padilla Morales](https://huggingface.co/antonypamo)
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**Framework:** Resonance of Reality Framework (RRF)
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**Phase:** Φ-series evolutionary model — Φ9.4
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---
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## 🧠 Model Description
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**ProSavantEngine Φ9.4** is a fine-tuned BERT-based model designed to align natural language with **geometric and resonant coherence principles**.
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It is trained to capture **semantic symmetry** and **information harmony** through a **Φ-weighted loss function** inspired by the golden ratio and icosahedral geometry.
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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.
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### Key Innovations
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- **Φ-weighted loss:** combines masked language modeling (MLM) with a golden-ratio-modulated coherence penalty.
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- **Icosahedral node embedding:** text samples are tagged `[NODE_1] ... [NODE_12]` representing discrete geometric symmetry anchors.
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- **Resonance alignment metric:** evaluates coherence across Fourier-transformed hidden-state spectra.
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- **Semantic-geometric fine-tuning:** aligns information representation to harmonic wave structures.
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---
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## 📚 Model Sources
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- **Repository:** [https://huggingface.co/antonypamo/ProSavantEngine_Phi9_4](https://huggingface.co/antonypamo/ProSavantEngine_Phi9_4)
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- **Base Model:** [`antonypamo/ProSavantEngine_Phi9_3`](https://huggingface.co/antonypamo/ProSavantEngine_Phi9_3)
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- **Dataset:** [`antonypamo/savantorganized`](https://huggingface.co/datasets/antonypamo/savantorganized)
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- **Framework Paper:** “Resonance of Reality Framework (RRF): Discrete Icosahedral Quantum Geometry and Unified Action through the Golden Ratio” — forthcoming on arXiv.
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---
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## 🔧 Model Details
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| Property | Value |
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|-----------|--------|
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| **Architecture** | BERT (6 layers, hidden size 384, 12 heads) |
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| **Objective** | Masked-language modeling + Φ-weighted resonance regularization |
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| **Hidden dropout** | 0.1 |
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| **Learning rate** | 3e-5 |
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| **Batch size** | 16 |
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| **Epochs** | 3 |
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| **Precision** | fp16 mixed |
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| **Activation** | GELU |
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| **Dataset size** | ~30k samples, balanced across 12 nodes |
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---
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## 💡 Intended Use
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### Direct Use
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Evaluate or enhance textual resonance, coherence, and meaning symmetry in:
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- Research papers
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- Philosophical or scientific writing
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- Generative model prompt optimization
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- Semantic alignment diagnostics
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### Downstream Use
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- Fine-tune for creative, linguistic, or cognitive AI systems requiring harmonic structure.
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- Integrate into symbolic reasoning frameworks or resonance-based cognitive architectures (e.g., Savant-ΩΦ).
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### Out-of-Scope
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- Real-time conversational agents without resonance normalization.
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- Factual QA or task-specific reasoning outside coherence evaluation.
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---
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## ⚠️ Bias, Risks, and Limitations
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This model captures **resonant semantics**, not truth or factual accuracy.
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It may amplify linguistic harmony while disregarding semantic correctness — making it *aesthetic-semantic*, not epistemic.
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It also reflects biases present in the original text corpus (scientific, philosophical, and poetic sources).
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### Recommendations
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Use Φ-coherence as a **complementary metric**, not a substitute for accuracy or ethical evaluation.
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---
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## 🧪 Training Details
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| Parameter | Value |
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|------------|--------|
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| **Dataset** | SavantOrganized (Φ-balanced) |
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| **Input format** | JSONL: {"text": "...", "node_id": n, "phi_score": x} |
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| **Loss** | MLM loss – 0.01 × Φ-coherence |
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| **Optimizer** | AdamW |
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| **Scheduler** | Linear warmup (5%) |
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| **Hardware** | NVIDIA A100 (40 GB) |
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| **Training time** | ~45 min (3 epochs) |
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| **Carbon footprint** | ≈ 0.3 kg CO₂eq |
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---
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## 📈 Evaluation
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| Metric | Description | Result |
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|---------|--------------|---------|
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| **Loss** | Final training loss | 0.023 |
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| **Avg Φ-score** | Mean coherence of eval set | 0.91 |
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| **Resonant ΔΦ** | ΔΦ between start/end epochs | +0.048 |
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| **Top tokens @MASK** | “φ”, “ψ”, “resonance”, “geometry”, “symmetry” |
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---
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## 🧮 Technical Architecture
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Φ-weighted loss = L_MLM − λ · (Φ-coherence)
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Φ-coherence = ⟨|FFT(H)|, cos(πf/φ)²⟩ / ||…||
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yaml
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Copy code
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Where *H* is the average hidden-state tensor across layers and *φ* = 1.618.
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The model thus maximizes linguistic energy alignment with geometric harmony.
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---
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## 🪐 Environmental Impact
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| Field | Value |
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|--------|-------|
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| **Hardware** | A100 GPU |
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| **Runtime** | 45 min |
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| **Region** | US Central |
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| **Carbon Emitted** | ≈ 0.3 kg CO₂eq |
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| **Frameworks** | Transformers 4.57.1, Datasets 3.0, PyTorch 2.9 |
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---
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## 🧾 Citation
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**BibTeX**
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```bibtex
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@software{padilla2025prosavantengine,
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author = {Padilla Morales, Antony},
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title = {ProSavantEngine Φ9.4 — Resonant Language Model},
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year = {2025},
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publisher = {Hugging Face},
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url = {https://huggingface.co/antonypamo/ProSavantEngine_Phi9_4}
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}
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APA
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Padilla Morales, A. (2025). ProSavantEngine Φ9.4 — Resonant Language Model. Hugging Face. https://huggingface.co/antonypamo/ProSavantEngine_Phi9_4
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🧭 Glossary
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Term Meaning
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Φ (phi) Golden ratio (≈ 1.618)
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Resonance Harmonic coherence between information and geometry
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Node Discrete icosahedral vertex representing a semantic domain
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ΔΦ Change in coherence during training
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🪄 Model Card Author
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Antony Padilla Morales
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Independent Researcher, Costa Rica
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📧 antonypamo@gmail.com
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🌐 https://huggingface.co/antonypamo
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© 2025 Antony Padilla Morales — Resonance of Reality Framework (RRF)
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