Hyperparameter Search
CommunityEfficiently tune BrainAI hyperparameters.
Authorsovr610
Version1.0.0
Installs0
System Documentation
What problem does it solve?
BrainAI hyperparameter tuning is complex due to multi-phase training, conditional parameters, and expensive evaluations; this skill provides an automated, reproducible workflow to discover effective configurations.
Core Features & Use Cases
- Phase-by-phase HPO for SNN, Encoders, HTM, Workspace, Decision, Reasoning, and Meta phases.
- LR finder integration to prune the search space by learning rate bounds.
- Bayesian optimization (TPE) and ASHA-based pruning with warm-starts and presets tailored for phase-specific tuning.
- Experiment logging, parameter importance estimation, and CSV export for analysis.
Quick Start
Run LR range test to bound learning rate and then launch a Bayesian optimization run with ASHA pruning for phase-wise BrainAI configurations.
Dependency Matrix
Required Modules
torch
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Hyperparameter Search Download link: https://github.com/sovr610/refffiy/archive/main.zip#hyperparameter-search Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 471,000+ vetted skills library on demand.