[[subsets]]

caption_extension = ".txt"

caption_tag_dropout_rate = 0.05

image_dir = "G:/dataset/concept/autopaizuri_under_clothes/11_aplong"

keep_tokens = 1

name = "11"

num_repeats = 11

random_crop_padding_percent = 0.05

shuffle_caption = true

[[subsets]]

caption_extension = ".txt"

caption_tag_dropout_rate = 0.05

image_dir = "G:/dataset/concept/autopaizuri_under_clothes/5_aphyper"

keep_tokens = 1

name = "5"

num_repeats = 5

random_crop_padding_percent = 0.05

shuffle_caption = true

[[subsets]]

caption_extension = ".txt"

caption_tag_dropout_rate = 0.05

image_dir = "G:/dataset/concept/autopaizuri_under_clothes/5_aptipout"

keep_tokens = 1

name = "5_1790613178385557300"

num_repeats = 5

random_crop_padding_percent = 0.05

shuffle_caption = true

[[subsets]]

caption_extension = ".txt"

caption_tag_dropout_rate = 0.05

image_dir = "G:/dataset/concept/autopaizuri_under_clothes/5_apunder"

keep_tokens = 1

name = "5_1790613178400564600"

num_repeats = 5

random_crop_padding_percent = 0.05

shuffle_caption = true

[train_mode]

train_mode = "lora"

[general_args.args]

persistent_data_loader_workers = true

vae_batch_size = 5

pretrained_model_name_or_path = ""

mixed_precision = "bf16"

gradient_checkpointing = true

gradient_accumulation_steps = 1

seed = 42

max_data_loader_n_workers = 1

max_token_length = 225

prior_loss_weight = 1.0

sdpa = true

max_train_epochs = 20

cache_latents = true

cache_latents_to_disk = true

[general_args.dataset_args]

resolution = 1024

batch_size = 5

[network_args.args]

network_dim = 32

network_alpha = 16.0

min_timestep = 0

max_timestep = 1000

network_train_unet_only = true

[optimizer_args.args]

optimizer_type = "ProdigyPlusScheduleFree"

lr_scheduler = "constant"

loss_type = "l2"

learning_rate = 1.0

unet_lr = 1.0

max_grad_norm = 1.0

[saving_args.args]

output_dir = "G:/LoRA_Easy_Training_Scripts/output"

output_name = "autopaizuri_under_clothes-anima1.0-V1-loha-dim32conv16AR0.5-NewTag"

save_precision = "bf16"

save_model_as = "safetensors"

save_every_n_epochs = 1

save_toml = true

save_toml_location = "G:/LoRA_Easy_Training_Scripts/output"

[logging_args.args]

log_prefix_mode = "disabled"

run_name_mode = "default"

[anima_args.args]

pretrained_model_name_or_path = "G:/sd-webui-forge-neo/models/Stable-diffusion/ANIMA/anima_baseV10.safetensors"

qwen3 = "G:/sd-webui-forge-neo/models/text_encoder/qwen_3_06b_base.safetensors"

vae = "G:/sd-webui-forge-neo/models/VAE/qwen_image_vae.safetensors"

qwen3_max_token_length = 512

t5_max_token_length = 512

timestep_sampling = "sigmoid"

sigmoid_scale = 1.0

[edm_loss_args.args]

edm2_loss_weighting = false

[bucket_args.dataset_args]

enable_bucket = true

min_bucket_reso = 256

max_bucket_reso = 2048

bucket_reso_steps = 64

[network_args.args.network_args]

conv_dim = 16

conv_alpha = 8.0

algo = "loha"

train_llm_adapter = "false"

[optimizer_args.args.optimizer_args]

betas = "0.95,0.99"

beta3 = "None"

weight_decay = "0"

weight_decay_by_lr = "True"

d0 = "2e-5"

d_coef = "1"

d_limiter = "True"

schedulefree_c = "0"

eps = "None"

split_groups = "True"

split_groups_mean = "False"

factored = "True"

factored_fp32 = "True"

use_bias_correction = "True"

use_stableadamw = "True"

use_schedulefree = "True"

use_speed = "False"

stochastic_rounding = "True"

fused_back_pass = "False"

use_cautious = "False"

use_grams = "False"

use_adopt = "False"

use_orthograd = "False"

use_focus = "False"