Software Engineering Courses (SECourses)•13mo ago

On my side, after extracting to LORA with rank 640 and 512, and converting to fp8, swarmui render bl

On my side, after extracting to LORA with rank 640 and 512, and converting to fp8, swarmui render black image. With rank 128 / 256 and 384,fp8 it's OK.

TTimson <@205854764540362752> what is the maximum number of dreambooth training steps yo...

Furkan Gözükara SECourses•12/17/24, 8:53 PM

i did over 50000 samples training

Furkan Gözükara SECourses•12/17/24, 8:53 PM

https://huggingface.co/MonsterMMORPG/Big_FLUX_Fine_Tuning_Experiments/tree/main

MonsterMMORPG/Big_FLUX_Fine_Tuning_Experiments at main

JJassim <@205854764540362752> im trying to use kohya ss to finetune sdxl on runpod using...

Furkan Gözükara SECourses•12/17/24, 8:54 PM

runpod initial load and setup sucks so bad

TTestitou On my side, after extracting to LORA with rank 640 and 512, and converting to fp...

Furkan Gözükara SECourses•12/17/24, 8:54 PM

interesting

Renzo•12/18/24, 2:17 AM

What settings are available to increase the speed of Dreambooth training? I'm very interested in experimenting with different configurations even if quality takes a hit. My understanding is that the configurations included in Kohya_FLUX_DreamBooth_v17 are meant to provide ways to fine tune models on different types of GPUs (vRAM).

RRenzo What settings are available to increase the speed of Dreambooth training? I'm ve...

Furkan Gözükara SECourses•12/18/24, 8:27 AM

yes

Furkan Gözükara SECourses•12/18/24, 8:28 AM

if you want speed only way is reducing resolution for fine tuning

Furkan Gözükara SECourses•12/18/24, 8:28 AM

which will reduce your quality

Renzo•12/18/24, 11:53 AM

Right. Or reducing the number of training photos.

Renzo•12/18/24, 12:38 PM

@Furkan Gözükara SECourses What about optimizers and other variables that could make the training converge to a good result quicker? Is Adafactor the best optimizer based on your testing?

QM•12/18/24, 8:17 PM

is there a particular reason behind using ohwx man?

QM•12/18/24, 8:17 PM

or are these just any random characters - with the objective to not use any characters that might have been present

RRenzo <@205854764540362752> What about optimizers and other variables that could make ...

Furkan Gözükara SECourses•12/19/24, 12:54 AM

Adafactor best for memory

Furkan Gözükara SECourses•12/19/24, 12:54 AM

each one requires a new research

QQM is there a particular reason behind using ohwx man?

Furkan Gözükara SECourses•12/19/24, 12:54 AM

ohwx is a rare token for clip

Furkan Gözükara SECourses•12/19/24, 12:54 AM

so i still use it

Hiramos_•12/19/24, 4:13 AM

@Furkan Gözükara SECourses Is it possible to perform DreamBooth training on a custom Flux checkpoint?

HHiramos_<@205854764540362752> Is it possible to perform DreamBooth training on a custom ...

Furkan Gözükara SECourses•12/19/24, 9:44 AM

yes

Furkan Gözükara SECourses•12/19/24, 9:44 AM

https://medium.com/@furkangozukara/thoroughly-experimented-with-fine-tuning-dreambooth-training-of-flux-dev-de-distill-pixelwave-13fab8c625bf

Medium

Thoroughly experimented with Fine-Tuning / DreamBooth training of F...

Thoroughly experimented with Fine-Tuning / DreamBooth training of Flux-dev-de-distill, PixelWave v03, Verus Vision and base FLUX Dev model…

Zhigarev•12/19/24, 11:38 AM

Does anyone here have experience creating the same DreamBooth character with different outfits? The problem is that when training in DreamBooth without captions, it's necessary to specify every clothing element to achieve the desired look, which heavily consumes tokens in the prompt and reduces adherence to the prompt during generation. Do you have any experience with this?

D4UNTLESS•12/19/24, 12:09 PM

@Furkan Gözükara SECourses hi
I'm about to do flux fine tuning on massed compute by following your tutorial but I have two questions:

1. What's the difference between a model fine tuned by using batch size of 1 and a model fine tuned by using a batch size of 7? How much (by percentage) is the 1 batch size better than the 7 batch size?
2. I'm fine tuning the model to train a realistic character. I have 410 training images. How many epochs should I go with if I use a batch size of 7? I need your best guess. In your tutorial, you mentioned that for 256 training images, 40 epoch is best for a batch size of 7

DD4UNTLESS <@205854764540362752> hi I'm about to do flux fine tuning on massed compute by f...

Furkan Gözükara SECourses•12/19/24, 12:45 PM

very small differnce

Furkan Gözükara SECourses•12/19/24, 12:45 PM

go with up to 50 epochs

Furkan Gözükara SECourses•12/19/24, 12:45 PM

and compare

FFurkan Gözükara SECourses Adafactor best for memory

Renzo•12/19/24, 12:52 PM

Interesting! I will experiment with AdamW today.

DD4UNTLESS <@205854764540362752> hi I'm about to do flux fine tuning on massed compute by f...

Timson•12/19/24, 2:33 PM

in my experience the more images are in the training set the more training steps is required to reach the same level of training.
For example 15 character image set is already good at 1800 steps (120 epochs), but with 50 images in training set the same level of training is achieved around 3200 steps (64 epochs)

Timson•12/19/24, 2:38 PM

SO the more images there are - the more generalised concept the model is learning - the more training steps required

Timson•12/19/24, 2:42 PM

IMO the sweet spot for character training is 25 images. With more images the training gets exponentially slower and the end result is not necessarily better

TTimson in my experience the more images are in the training set the more training steps...

Furkan Gözükara SECourses•12/19/24, 3:35 PM

true

TTimson IMO the sweet spot for character training is 25 images. With more images the tra...

Furkan Gözükara SECourses•12/19/24, 3:35 PM

it depends your aims

FFurkan Gözükara SECourses it depends your aims

D4UNTLESS•12/19/24, 4:27 PM

Thanks for the reply earlier. I previously trained a flux lora following your tutorial and used one of your configs with 100 training images and 31 epochs. It achieved (to some extent) what I was looking for (a slightly different face but same body) but only missed the mark at body consistency. So, this time I'm looking to get something better by finetuning instead of lora. I want a slight variation in face but 90-100% body consistency. As said before, I'm using 410 images. So will I achieve my targets with 50 epochs? Thanks!

FFurkan Gözükara SECourses yes

Hiramos_•12/19/24, 6:30 PM

Thank you!

DD4UNTLESS Thanks for the reply earlier. I previously trained a flux lora following your tu...

Furkan Gözükara SECourses•12/19/24, 9:11 PM

yes should be sufficient

Furkan Gözükara SECourses•12/19/24, 9:11 PM

410 images really a lot

FFurkan Gözükara SECourses yes should be sufficient

D4UNTLESS•12/19/24, 9:18 PM

Thanks! One final question. My images are in different resolutions and cannot be cropped. You can see some of the resolutions in the image. Can I train on these resolutions or just 1024x1024?