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---
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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