if still was low quality either dataset is not good
if still was low quality either dataset is not good
Fdifferent person?=
Asame face
NWhen using regularization image sets, can I just use the set for the resolution I use all the time? I almost never render at 512x for example, always 1024 or higher. Or should I still use all the sets?
Fok then your dataset either not good
For you made mistake
ISir please make a tutorial on how to do masked training
Fuse same resolution as your training images
Fyep it is in production
Fthat is why i researched
Fsadly people didnt even upvote
FReddit
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IThank you sir will waiting fir the release
NI thought because OneTrainer allows different resolutions, it would be the same for regularization images. I'm not to that part of the tutorial yet lol.
Fwell there are 2 sceneraios
Feither they get full resized
For resized into buckets
Fdepending on your setup
Fif you manually set all equal size
II did upvote
Fyou get more control
Fi prefer 1024x1024
Fthank you
NJust for clarification, your regularization images are mostly of people of color, and I'm training an east Asian and white person mostly. The ethnicity of the people in the regularization images don't have an effect on the training, right? Regularization images are for help with poses?
Edit: just looked at the latest folder of regularization images and it's a really good mix of different ethnicities, so I guess you can ignore this question, lol.
Edit: just looked at the latest folder of regularization images and it's a really good mix of different ethnicities, so I guess you can ignore this question, lol.
Fwell as much as deverse better
Fyes i tried to collect from every nation
NYou did a great job.
NI honestly don't know where you get the energy and drive to do all these things. It must have taken forever just to gather all those images!
Fi am full time spending on these right now 
so patreon support is my almost whole revenue
so patreon support is my almost whole revenue
Ki gotchuu 
K2 upvotes fromf both my accs 
None from me, as well lol
N@Dr. Furkan Gözükara Maybe every time you make a new post on reddit, you send out a server-wide note and ask people to upvote it?
Fnah this is fine. nevermind reddit :d
NWith an RTX 4070 12gb, training 1024x at float16 using your tier1sdxl 10gb config, do you know a rough estimate of how long it would take to train using 25 images? Just a ballpark figure. I'm wondering if I should I set it and leave the house to run errands for a few hours, or if I should set it and leave it to run overnight.
Fyou can calculate
Fwhat is your second / it
NAround 3.6 to 3.9
Fok lets say 4 at worst
Fso 25 images with lets say 140 epoch
F25 * 140 * 2 = 7000 steps
Fso it would be 7000 * 4 / 60 / 60 = 7.8 hours
NOvernight it is, then! Thanks for doing the math for me. I can do the math, I just don't enjoy the process, lol.
NAlthough looking at cmd, it looks like I'm averaging around 2s/it - so maybe if I'm lucky, around 4 hours
NSo I stopped the training at 3100 and tested the saved model, and if I use all the common tags from the training in the same prompt, I get a pretty damned good result. But if I remove all or even just some of those common tags, or if I try to use any kind of creative prompt (like "sitting in a golden throne wearing golden armor"), the face likeness goes away.
Frecording onetrainer tutorial already over 2 hours
Fdid you train with captions?
FPatreon
Get more from SECourses: Tutorials, Guides, Resources, Training, MidJourney, Voice Clone, TTS, ChatGPT, GPT, LLM, Scripts by Furkan Gözükara on Patreon
NYes, that means the model you're using for inference of that word "boob" is still trained "stronger" than your LoRA concept. If you're training say the concept "girlfriend woman" with captions on your dataset you could leave out any reference to breasts. However it may make your LoRA less flexible. You could also experiment with doing the caption dropout option (available in Kohya) or for an experiment train your LoRA with no captions and see if the accuracy increases...
Chello i have a question
i have 2000 reg images
which should i use？
30 images 1 reg
or
30 images 30 reg
i have 2000 reg images
which should i use？
30 images 1 reg
or
30 images 30 reg
NAhhh, that makes sense! I created the training data before watching the tutorial, so I forgot that the caption text was included in the folder with the training images already. Damn it, back to the drawing board, lol.