u/AuthurAndersson

The style lora has 2200 images.
There are a couple of different concepts in it the model is not train on prior such as specific types of hats or purses.

How should I tackle this problem? Atm I am running this with a batch size of 2 and a gradient accumulation of 2. I could increase this to 3:3 I guess.

Anyone got any experience training larger LORAs?

I could alternatively, not perfect, splice the training data into style:concepts and just train multiple smaller concepts and pipe them in whenever I need them - negative part is of course that this would be quite a hassle. I'd probably end up having to setup a semantic RAG database and make the LLM finetune each of my prompts (really not ideal).