Using Prodigy to train SDXL loras specifically, is it possible to force a smaller learning rate for the TE or UNET only? Something like adjusting the d_coef, but only for one of them.
Please try out the version in this pull request, it supports different LR values for different layers via setting the layer_scale for each in the param group:
https://github.com/konstmish/prodigy/pull/9
Using Prodigy to train SDXL loras specifically, is it possible to force a smaller learning rate for the TE or UNET only? Something like adjusting the d_coef, but only for one of them.