Iori Yoshizuki ( (IA)^3 experiment version ) - I''s

prodigy 및 Type Ia3을 사용하여 다음 매개변수로 학습되었습니다:

[general_args.args]
pretrained_model_name_or_path = "D:/wifediff/stable-diffusion-webui/models/Stable-diffusion/anything-v4.5-pruned.safetensors"
mixed_precision = "fp16"
seed = 80085
clip_skip = 2
xformers = true
max_data_loader_n_workers = 1
persistent_data_loader_workers = true
max_token_length = 225
prior_loss_weight = 1.0
max_train_epochs = 8
training_comment = "Trigger: yoshizuki_iori, School_uniform_Purple_shirt_Blue_skirt_White_neckerchief_Black_thighhighs"
cache_latents = true

[general_args.dataset_args]
resolution = 512
batch_size = 1

[network_args.args]
network_dim = 32
network_alpha = 16.0

[optimizer_args.args]
optimizer_type = "Prodigy"
lr_scheduler = "cosine"
learning_rate = 1.0
lr_scheduler_type = "LoraEasyCustomOptimizer.CustomOptimizers.CosineAnnealingWarmupRestarts"
lr_scheduler_num_cycles = 1
min_snr_gamma = 5

[saving_args.args]
output_dir = "D:/wifediff/lora/iorilora"
save_precision = "fp16"
save_model_as = "safetensors"
output_name = "yoshizuki_ioriV4"
tag_occurrence = true
save_toml = true
save_every_n_epochs = 1

[bucket_args.dataset_args]
enable_bucket = true
min_bucket_reso = 256
max_bucket_reso = 1024
bucket_reso_steps = 64

[network_args.args.network_args]
conv_dim = 32
conv_alpha = 16.0
algo = "ia3"

[optimizer_args.args.lr_scheduler_args]
min_lr = 1e-6
gamma = 0.9

[optimizer_args.args.optimizer_args]
weight_decay = "0.01"
decouple = "True"
use_bias_correction = "True"
safeguard_warmup = "True"
d_coef = "2"