mitarashi_santa/mitarashi_santa.toml

[[subsets]]
caption_extension = ".txt"
image_dir = "E:/Everything artificial intelligence/loradataset/5_ohwx mitarashi_santa"
name = "5_ohwx mitarashi_santa"
num_repeats = 5

[general_args.args]
max_data_loader_n_workers = 1
persistent_data_loader_workers = true
vae = "E:/Everything artificial intelligence/stable-diffusion-webui/models/VAE/sdxl_vae.safetensors"
sdxl = true
mixed_precision = "fp16"
gradient_checkpointing = true
seed = 23
max_token_length = 225
prior_loss_weight = 1.0
xformers = true
cache_latents = true
pretrained_model_name_or_path = "E:/Everything artificial intelligence/stable-diffusion-webui/models/Stable-diffusion/SDXL/animagine-xl-3.1.safetensors"
max_train_epochs = 15

[general_args.dataset_args]
resolution = 1024
batch_size = 2

[network_args.args]
ip_noise_gamma = 0.1
network_dropout = 0.3
network_dim = 16
network_alpha = 8.0
min_timestep = 0
max_timestep = 1000

[optimizer_args.args]
lr_scheduler = "cosine"
optimizer_type = "AdamW8bit"
lr_scheduler_type = "LoraEasyCustomOptimizer.CustomOptimizers.CosineAnnealingWarmupRestarts"
lr_scheduler_num_cycles = 2
learning_rate = 0.001
warmup_ratio = 0.15
text_encoder_lr = 1e-6
scale_weight_norms = 5.0
max_grad_norm = 1.0
min_snr_gamma = 8

[saving_args.args]
save_precision = "fp16"
save_model_as = "safetensors"
save_every_n_epochs = 1
save_toml = true
output_dir = "E:/Everything artificial intelligence/stable-diffusion-webui/models/Lora/mitarashi_santa"
save_toml_location = "E:\\Everything artificial intelligence\\stable-diffusion-webui\\models\\Lora\\mitarashi_santa"
output_name = "mitarashi_santa"

[noise_args.args]
noise_offset = 0.0357

[bucket_args.dataset_args]
enable_bucket = true
bucket_no_upscale = true
min_bucket_reso = 512
max_bucket_reso = 2048
bucket_reso_steps = 64

[network_args.args.network_args]
conv_dim = 24
conv_alpha = 12.0

[optimizer_args.args.lr_scheduler_args]
min_lr = 1e-6
gamma = 0.85

[optimizer_args.args.optimizer_args]
weight_decay = "0.05"
betas = "0.9,0.99"