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hyperparameters

Complete guide to SimPO hyperparameter selection and tuning.

  • Skills
  • AI research
  • 0

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

  1. Install the skill (command above).
  2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
  3. No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/hyperparameters && curl -fsSL https://doutorai.pt/data/lib/skills__hyperparameters.md -o .claude/skills/hyperparameters/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Hyperparameters

Complete guide to SimPO hyperparameter selection and tuning.

## Overview

Key hyperparameters in SimPO:
1. **Learning Rate** - Most critical
2. **Beta (β)** - Reward scaling
3. **Gamma-Beta Ratio (γ/β)** - Target margin
4. **SFT Weight** - Regularization strength

## Learning Rate

### Recommended Ranges

**By model size**:
| Model Size | Learning Rate | Notes |
|------------|---------------|-------|
| 1B-3B | 5e-7 to 1e-6 | Higher end safe |
| 7B-8B | 3e-7 to 5e-7 | **Standard** |
| 13B-30B | 1e-7 to 3e-7 | Lower for stability |
| 70B+ | 5e-8 to 1e-7 | Very conservative |


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