Yuuki Sakuna Pony LoRA

Version 2 description

• using Experimental Optimizer (it seems improvement on full body but camera angle still not variable if not prompt it)

• bow still remains even change outfit

Version 1 description

• I like cat ears girl so, I trained as LoRA (don't know about her past at all :<)

Trigger Word

• trigger word

yuuki sakuna

• any costume (still not flexible enough)

yuuki sakuna, long hair, animal ears, pink hair, blush, cat ears, pink eyes, two side up, ahoge, colored inner hair, two-tone hair

• debut costume (good but some component still missing)

yuuki sakuna, long hair, hair ornament, bow, animal ears, pink hair, blush, cat ears, maid headdress, hair bow, frills, hairclip, pink eyes, pink bow, blue bow, maid, puffy sleeves, two side up, cat hair ornament, ahoge, heart hair ornament, puffy short sleeves, clothing cutout, pink dress, blue bow, colored inner hair, two-tone hair, cleavage, breasts

• for full body add this following text will help (shoes still not correct)

shoes, black footwear, white thighhighs

Limitations

• Cannot change costume properly (still have some debut costume component leftover)

• full body may be not effective

• LoRA still little bit underfitting (like medium rare pork) (in version 1)

• version 2 is improve some small detail but dataset still not variable enough (due to imbalance image)

Training Details (Version 2)

LoRA size

• reduced dimension to 8 with dynamic alpha

dataset

• 38 images (most is half body)

parameters

• resolution = 1024

• batch size = 2

• dim,alpha = 16,16 (for training)

• mix/save precision = bf16/bf16

• optmizer = AdEMAMix (32 bit consume VRAM)

• UNet LR = 2e-4

• TE LR = 1e-4

• scheduler = inverse_sqrt with warmup 100 steps

• l2 loss only

steps

• epochs = 10

• total steps = 2850

• repeat = 15 (one concept only)

tools

• kohya-ss GUI v24.2.0

• torch 2.5.0 cu124

• RTX 3060 12 GB + xformers + gradient_checkpointing

weight

• UNet weight average strength = 0.015634962041489377

• Text Encoder (1) weight average strength Clip_L = 0.011193290141749815

• Text Encoder (2) weight average strength Clip_G = 0.010691167576002698

Training Details (Version 1)

dataset

• 38 images (most is half body)

parameters

• resolution = 1024

• batch size = 2

• dim,alpha = 16,16 (no resize for preserving quality if LoRA is good enough will do it :P)

• mix/save precision = bf16/fp16 (accidentally change)

• optmizer = AdEMAMix8bit

• UNet LR = 1e-4

• TE LR = 5e-05

• scheduler = inverse_sqrt with warmup 100 steps

• huber snr with c = 0.85

steps

• epochs = 10

• total steps = 2850

• repeat = 15 (one concept only)

• full_bf16 training

tools

• kohya-ss GUI v24.2.0

• torch 2.5.0 cu124

• RTX 3060 12 GB + xformers + gradient_checkpointing

weight

• UNet weight average strength = 0.008335085569112463

• Text Encoder (1) weight average strength Clip_L = 0.0073367764333498705

• Text Encoder (2) weight average strength Clip_G = 0.005826970830639767

description ref from Gtonero

*This LoRA is for studying LoRA training with new technique so do not use for damaging the vtuber (also support her too).