Modelpublic

Invictus-AI/self-evolving-nn

sourceHugging Faceupdated 2mo agoView on Hugging Face

0likes2downloads

Model Card

🧬 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.