Good morning, I have a question about training multiple characters in a single LORA. A few weeks ag
Good morning, I have a question about training multiple characters in a single LORA.
A few weeks ago, you mentioned that when captions are added to images (and these include the concept, for example, ohwx), the class token from the name of the directory where the images are stored is no longer used. That is, the 'ohwx' part of '20_ohwx' is not used, only the '20' is used to determine repetitions.
Based on this, if I want to train multiple characters, which strategy is better?
a) One folder for each character, even if they all have captions.
b) A single folder that encompasses all characters.
On another note, let's assume that for character1 I have 50 images and for character2 I have 100 images. Should this be taken into account in some way? For example, adjusting the repetitions so that the multiplication of repetition and number of images is similar across all datasets, or would this be counterproductive, and could it cause the dataset with fewer images and more repetitions to be overfitted compared to the rest?
Best regards and sorry for the long message
A few weeks ago, you mentioned that when captions are added to images (and these include the concept, for example, ohwx), the class token from the name of the directory where the images are stored is no longer used. That is, the 'ohwx' part of '20_ohwx' is not used, only the '20' is used to determine repetitions.
Based on this, if I want to train multiple characters, which strategy is better?
a) One folder for each character, even if they all have captions.
b) A single folder that encompasses all characters.
On another note, let's assume that for character1 I have 50 images and for character2 I have 100 images. Should this be taken into account in some way? For example, adjusting the repetitions so that the multiplication of repetition and number of images is similar across all datasets, or would this be counterproductive, and could it cause the dataset with fewer images and more repetitions to be overfitted compared to the rest?
Best regards and sorry for the long message






