---
license: mit
tags:
  - automl
  - genetic-programming
  - loss-functions
  - neural-networks
  - bittensor
datasets:
  - synapz/automl-genes
---

# AutoML Evolved Loss Functions

This repository contains evolved neural network loss functions discovered through distributed genetic programming on the Bittensor network (subnet 49 Hivetrain AutoML).

## 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)

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