Open BelieveDiffusion opened 1 month ago
flux_train.py doesn't support CLIP-L/T5XXL training yet. The script should only save Flux model.
Oh! Thank you for the help, and sorry for the misunderstanding. Perhaps it was the Flux model training rate that was too high. I will perform some more experiments.
Hello! I'm using flux_train.py from the sd3 branch to fine-tune Flux on a custom data set. It's working, but I'm finding that the text encoders are getting over-trained very quickly. I think this is because I can't set a separate (much lower) training rate for the text encoders, and so the text encoders have to use the high UNet training rate. There also doesn't seem to be a way to opt out of text encoder training with the fine-tune script.
I saw that it is possible in flux_train_network.py to specify different text encoder rates for LoRA training. Is there any chance you could add separate text encoder learning rates for the fine-tune script too, or make it possible to opt out of TE training?