Hello everyone. I am Dr. Furkan Gözükara. PhD Computer Engineer. SECourses is a dedicated YouTube channel for the following topics : Tech, AI, News, Science, Robotics, Singularity, ComfyUI, SwarmUI, ML, Artificial Intelligence, Humanoid Robots, Wan 2.2, FLUX, Krea, Qwen Image, VLMs, Stable Diffusion
I tried switching to prodigy optimizer setting learning rate to 1 and cosine. With 60 images using basic tag captions, 150 epoch, batch 4 the result was very amazing and fast.
there are other parameters I am testing now (dropout, weight decay, further refining d coef) as well as changing batch size/repeats/epochs to see if I can arrive at a good setup
Thank you for expanding on your experiments. Are you using an LLM to guide you through tunning parameters such as dropout or weight decay? I wonder if SOTA LLMs can help us arrive at the optimal ones faster than doing it on our own.
getting close - in fact I think i have it the only problem I have now is the problem I always have which is with unique features getting lost (moles on specific sides of faces, or heterochromia, etc.)