---
tags:
- image-classification
- cantor-fusion
- geometric-deep-learning
- safetensors
- vision-transformer
- warm-restarts
- geometric-coalescence
library_name: pytorch
datasets:
- cifar10
- cifar100
metrics:
- accuracy
---

# vit-beans-v3

**Geometric Deep Learning with Cantor Multihead Fusion + Shatter-Reconstruct Training**

This repository contains training runs using Cantor fusion architecture with:
- Pentachoron (5-simplex) structures for geometric routing
- CosineAnnealingWarmRestarts for exploration cycles
- GeometricCoalescenceLoss for shatter-reconstruct training

### 🚀 LR Boost + Geometric Coalescence
This run uses **restart_lr_mult = 1.15x** with **GeometricCoalescenceLoss**:
- LR boosts create aggressive exploration cycles
- Coalescence loss provides geometric scaffolding during weight thrashing
- Adaptive weighting: 0.1 → 0.8 during LR spikes
- Model reconstructs from geometric first principles when patterns shatter


## Current Run

**Latest**: `cifar100_weighted_ADAMW_WarmRestart_boost1.15x_coal0.5_20251124_152227`
- **Dataset**: CIFAR100
- **Fusion Mode**: weighted
- **Coalescence**: λ=0.5 ✓
- **LR Boost**: 1.15x 🚀

---

**Repository maintained by**: [@AbstractPhil](https://huggingface.co/AbstractPhil)