Improve Automatic Configuration Setup

Improve the automatic configuration setup so users don't have to manually configure every training parameter. Suggested improvements Automatically detect the dataset type and structure. Automatically select suitable training parameters based on the available data. Provide sensible default values for common settings. Detect available hardware and adjust configuration accordingly. Automatically validate the configuration before training starts. Show the detected configuration and allow users to modify it when needed. Provide clear warnings when a configuration may cause errors or poor results. The goal is to make the setup process more automatic, beginner-friendly, and reliable, while still allowing advanced users to customize the configuration.