Using synthetic training data to improve Flux finetunes

Synthetic training data improves Flux finetunes by providing more controlled and diverse examples for model refinement. This approach reduces reliance on real-world datasets, which can be scarce or biased. The method enables more consistent output quality across different finetuning scenarios.