This is a training of a public LoRA style (2 seperate training each on 4x A6000).

Experimenting captions vs non-captions. So we will see which yields best results for style training on FLUX.

Generated captions with multi-GPU batch Joycaption app.

I am showing 5 examples of what Joycaption generates on FLUX dev. Left images are the original style images from the dataset.

I used my multi-GPU Joycaption APP (used 8x A6000 for ultra fast captioning)

https://www.patreon.com/posts/110613301

The no caption dataset uses only ohwx 3d render as caption

Total step count is being 500 * 114 / 4 (4x GPU - batch size 1) = 14250

Taking 37 hours currently if I don't terminate early

Will save a checkpoint once every 25 epochs

Hopefully will share trained LoRA on Hugging Face and CivitAI along with full dataset including captions.

I got permission to share dataset but can't be used commercially.

Also I will hopefully share full workflow in the CivitAI and Hugging Face LoRA pages.

So far 450 epochs completed