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README.md

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-license: mit
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+# AutoML Evolved Loss Functions
+
+This repository contains evolved neural network loss functions discovered through distributed genetic programming on the Bittensor network (subnet 43).
+
+## Overview
+
+The genes stored here represent novel loss functions optimized for:
+- Image classification tasks
+- Neural network training efficiency
+- Improved convergence rates
+
+## Repository Structure
+/automl-genes ├── losses/ # Evolved loss function implementations ├── metrics/ # Performance metrics and evaluations └── metadata/ # Gene genealogy and evolution data
+
+
+## Technical Details
+
+Loss functions are evolved using:
+- Genetic programming with population size 100
+- Tournament selection (size 3)
+- Multi-architecture validation across:
+  - MLP
+  - ResNet
+  - MobileNet V3
+  - EfficientNet V2
+
+## Usage
+
+The evolved loss functions can be imported and used as drop-in replacements for standard PyTorch loss functions in deep learning projects.
+
+## Project
+
+Part of the Hivetrain AutoML subnet focused on discovering improved neural network components through distributed evolution.
+
+For more information, visit:
+- [DistributedAutoML Repository](https://github.com/Hivetensor/DistributedAutoML)
+- [Hivetrain Discord](https://discord.gg/JpRSqTBBZU)
+
+
+---
+license: mit
+---