Software Engineering Courses (SECourses)•3y ago

gives me this error for some reason I dont know why

RRen I am using A100

Furkan Gözükara SECourses•12/26/23, 7:37 PM

you can use our dreambooth config

Furkan Gözükara SECourses•12/26/23, 7:37 PM

however for product training the dataset matters a lot

AAIGambino gives me this error for some reason I dont know why

Furkan Gözükara SECourses•12/26/23, 7:37 PM

i would say reinstall

Furkan Gözükara SECourses•12/26/23, 7:38 PM

do a fresh one

Furkan Gözükara SECourses•12/26/23, 7:38 PM

library missing

Furkan Gözükara SECourses•12/26/23, 7:38 PM

or you need to activate venv and install missing library manually

AIGambinoOP•12/26/23, 7:47 PM

tried manually installing bitsandbytes no luck

FFurkan Gözükara SECourses try to reduce VRAM usage before starting training

DigitalArt_Lover•12/26/23, 8:48 PM

I 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

DDigitalArt_Lover I didn't run anything else, while starting the training. I've a core i9 cpu an...

Furkan Gözükara SECourses•12/26/23, 9:09 PM

it is using shared vram

Furkan Gözükara SECourses•12/26/23, 9:09 PM

you need to use our 16gb config

Furkan Gözükara SECourses•12/26/23, 9:09 PM

enable xformers and gradient checkpointing

FFurkan Gözükara SECourses i would say reinstall

AIGambinoOP•12/26/23, 9:35 PM

Reinstall stable diffusion? I tried activating venv and that didn't do anything

AAIGambino Reinstall stable diffusion? I tried activating venv and that didn't do anything

Furkan Gözükara SECourses•12/26/23, 9:39 PM

it is kohya

FFurkan Gözükara SECourses it is kohya

AIGambinoOP•12/26/23, 10:04 PM

AAIGambino Click to see attachment

Furkan Gözükara SECourses•12/26/23, 10:05 PM

restart

Furkan Gözükara SECourses•12/26/23, 10:05 PM

also your antivirus could be problem

Zax•12/26/23, 10:10 PM

Hello! 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.

AIGambinoOP•12/26/23, 10:11 PM

Disabled the AV.

AIGambinoOP•12/26/23, 10:27 PM

well this is as far as I can get it hangs here

ZZax Hello! New here. Dreambooth training question. If I'm trying to train a model on...

Furkan Gözükara SECourses•12/26/23, 10:43 PM

have you tried our reg images?

Furkan Gözükara SECourses•12/26/23, 10:43 PM

it has mixed body types

AAIGambino well this is as far as I can get it hangs here

Furkan Gözükara SECourses•12/26/23, 10:43 PM

good working

FFurkan Gözükara SECourses have you tried our reg images?

Zax•12/26/23, 10:50 PM

hm, 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)

Zax•12/26/23, 10:51 PM

also, 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?

Zax•12/26/23, 10:53 PM

oh yeah these images are way more diverse. Ethnicities, ages, body shapes. I'll have a try with these. Thanks!

ZZax hm, I will take a look at your reg images, I'd been using Aitrepreneur's images ...

Furkan Gözükara SECourses•12/26/23, 10:53 PM

my images are manually collected

Furkan Gözükara SECourses•12/26/23, 10:53 PM

i spent over 5 days

ZZax also, do you have tips for number of images vs repeats? Is there some target I'm...

Furkan Gözükara SECourses•12/26/23, 10:53 PM

i suggest repeat 200

Furkan Gözükara SECourses•12/26/23, 10:54 PM

and save based number of steps

Furkan Gözükara SECourses•12/26/23, 10:54 PM

so 1 epoch

Furkan Gözükara SECourses•12/26/23, 10:54 PM

200 repeat

Zax•12/26/23, 10:54 PM

repeat 200 regardless of the number of images?

ZZax repeat 200 regardless of the number of images?

Furkan Gözükara SECourses•12/26/23, 10:54 PM

how many train images you have?

Zax•12/26/23, 10:54 PM

Furkan Gözükara SECourses•12/26/23, 10:54 PM

ok it is quite a lot

Furkan Gözükara SECourses•12/26/23, 10:55 PM

make repeat 130

Furkan Gözükara SECourses•12/26/23, 10:55 PM

because otherwise you will need more reg images

Furkan Gözükara SECourses•12/26/23, 10:55 PM

also 130 epoch is decent for 39 images

Zax•12/26/23, 10:55 PM

is there an ideal ratio of reg images to training images?

ZZax is there an ideal ratio of reg images to training images?

Furkan Gözükara SECourses•12/26/23, 10:55 PM

actually the more you use it is better

Furkan Gözükara SECourses•12/26/23, 10:55 PM

therefore we try to use max

Furkan Gözükara SECourses•12/26/23, 10:55 PM

but as you do more repeat

Furkan Gözükara SECourses•12/26/23, 10:55 PM

it will do more epochs

Furkan Gözükara SECourses•12/26/23, 10:55 PM

200 repeat actually means 200 epoch

Furkan Gözükara SECourses•12/26/23, 10:56 PM

not exactly due to scripts random image training logic but almost equal

Zax•12/26/23, 10:57 PM

ok 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?

ZZax ok so 130*39=5070, which is close to 5200 which is the number of regularization ...

Furkan Gözükara SECourses•12/26/23, 10:58 PM

ye i calculated that way

Furkan Gözükara SECourses•12/26/23, 10:59 PM

but it could lead to overtraining

Furkan Gözükara SECourses•12/26/23, 10:59 PM

since it will be equal to

Furkan Gözükara SECourses•12/26/23, 10:59 PM

130 * 39 * 2 steps

gives me this error for some reason I dont know why

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