i would say reinstall
i would say reinstall
Fdo a fresh one
Flibrary missing
For you need to activate venv and install missing library manually
Atried manually installing bitsandbytes no luck
DI didn't run anything else, while starting the training.
I've a core i9 cpu and a 4080 (16gb vram gpu).
I think in terms of my power, this 3000 steps should take a lot less time to train??
Again, I've used regularization images and also using a concept folder as well.
The settings are below:
Train Batch Size: 1
Epoch: 1
repeats for training images: 20.
repeats for regularization images: 2.
And for the concept folder: Training steps per concept per epoch is 20.
Mixed precision: fp16
Save precision: fp16
I've a core i9 cpu and a 4080 (16gb vram gpu).
I think in terms of my power, this 3000 steps should take a lot less time to train??
Again, I've used regularization images and also using a concept folder as well.
The settings are below:
Train Batch Size: 1
Epoch: 1
repeats for training images: 20.
repeats for regularization images: 2.
And for the concept folder: Training steps per concept per epoch is 20.
Mixed precision: fp16
Save precision: fp16
Fit is using shared vram
Fyou need to use our 16gb config
Fenable xformers and gradient checkpointing
AReinstall stable diffusion? I tried activating venv and that didn't do anything
Fit is kohya
A
Frestart
Falso your antivirus could be problem
ZHello! New here. Dreambooth training question. If I'm trying to train a model on images of a woman who doesn't have a thin body type, is having regularization images of thin women influencing the training towards a thin body type? I've been banging my head on this training for 3 days now with no real success.
ADisabled the AV.
Awell this is as far as I can get it hangs here
Fhave you tried our reg images?
Fit has mixed body types
Fgood working
Zhm, I will take a look at your reg images, I'd been using Aitrepreneur's images but it looks like your dataset is much larger (5200 images vs 1000 for his)
Zalso, do you have tips for number of images vs repeats? Is there some target I'm aiming for like images*repeats=500, or something like that?
Zoh yeah these images are way more diverse. Ethnicities, ages, body shapes. I'll have a try with these. Thanks!
Fmy images are manually collected
Fi spent over 5 days
Fi suggest repeat 200
Fand save based number of steps
Fso 1 epoch
F200 repeat
Zrepeat 200 regardless of the number of images?
Fhow many train images you have?
Z39
Fok it is quite a lot
Fmake repeat 130
Fbecause otherwise you will need more reg images
Falso 130 epoch is decent for 39 images
Zis there an ideal ratio of reg images to training images?
Factually the more you use it is better
Ftherefore we try to use max
Fbut as you do more repeat
Fit will do more epochs
F200 repeat actually means 200 epoch
Fnot exactly due to scripts random image training logic but almost equal
Zok so 130*39=5070, which is close to 5200 which is the number of regularization images. Is that number similarity a coincidence or is that what I'm aiming for, for the number of repeats multiplied by the number of images to be about equal to the number of reg images?
Fye i calculated that way
Fbut it could lead to overtraining
Fsince it will be equal to
F130 * 39 * 2 steps
Fusually 15 images with 150 repeat yields good results even little bit overtrained for realism
A
Fmust be out of vram