# 🧬 Self-Evolving Neural Network — 4524d43d

Evolved locally with neuroevolution (genetic architecture search), then uploaded from this machine.

## Model

- **Architecture**: gated MLP — top-3 features → layer 1, remaining features join every layer after
- **Layers**: `192(swish), 96(selu), 32(swish), 192(linear), 256(relu), 64(sigmoid)`
- **Params**: 102,216
- **Learning rate**: 0.005 · **Optimizer**: rmsprop · **Batch size**: 16
- **Top-3 feature gate**: [4, 9, 16]
- **Fitness**: 331118.82

## Evolution history

- **Generations**: 18
- **Initial best fitness**: 37948.7707
- **Final best fitness**: 240545.7623
- **Improvement**: +533.9%

## Files

| File | Description |
|------|-------------|
| `evo_checkpoints/best_model.keras` | Trained best model (Keras) |
| `evo_checkpoints/best_genome.json` | Best architecture genome |
| `evo_checkpoints/evolution_history.json` | Fitness across generations |
| `self_evolving_model.py` | Core evolution engine |
| `evo_gui.py` | Flask web dashboard |
| `requirements.txt` | Dependencies |

## How to run

```bash
pip install -r requirements.txt
# Continue evolving from this state
python3 self_evolving_model.py --continue --generations 50
# Or launch the web GUI
python3 evo_gui.py --port 5000
```

## Scaling up (v2/v3 on GPU)

```bash
python3 self_evolving_model.py --continue --max-units 512 --max-layers 8 --train-epochs 20
```
See `evo_v2_colab.ipynb` for a ready-to-run Google Colab notebook.