i would like to learn deeply about fine-tuning local models before burning money

A user is seeking practical guidance on fine-tuning local models, specifically mentioning techniques like RL, RL LoRA, QLoRA, and CPT LoRA. They want to understand these concepts in depth to successfully fine-tune models such as qwen 27b on a custom corpus without incurring significant costs due to incorrect technique selection or parameter choices like Rank count, which can lead to lengthy re-runs.