[network_arguments]
unet_lr = 6e-5
text_encoder_lr = 1e-6
network_dim = 16
network_alpha = 8
network_module = "networks.lora"
network_train_unet_only = false

[optimizer_arguments]
learning_rate = 6e-5
lr_scheduler = "cosine"
lr_scheduler_type = "LoraEasyCustomOptimizer.RexAnnealingWarmRestarts.RexAnnealingWarmRestarts"
lr_scheduler_args = [ "min_lr=1e-9", "gamma=0.9", "d=0.9", "first_cycle_max_steps=1240",]
optimizer_type = "LoraEasyCustomOptimizer.came.CAME"
optimizer_args = [ "weight_decay=0.04",]
loss_type = "l2"
max_grad_norm = 1.0

[training_arguments]
lowram = true
pretrained_model_name_or_path = "/content/Illustrious-XL-v0.1.safetensors"
vae = "/content/sdxl_vae.safetensors"
max_train_epochs = 10
train_batch_size = 8
seed = 42
max_token_length = 225
xformers = false
sdpa = true
min_snr_gamma = 8.0
ip_noise_gamma = 0.05
no_half_vae = true
gradient_checkpointing = true
gradient_accumulation_steps = 1
max_data_loader_n_workers = 1
persistent_data_loader_workers = true
mixed_precision = "bf16"
full_bf16 = true
full_fp16 = false
cache_latents = true
cache_latents_to_disk = true
cache_text_encoder_outputs = false
min_timestep = 0
max_timestep = 1000
prior_loss_weight = 1.0
multires_noise_iterations = 6
multires_noise_discount = 0.3

[saving_arguments]
save_precision = "fp16"
save_model_as = "safetensors"
save_every_n_epochs = 1
save_last_n_epochs = 4
output_name = "fubuki_illus"
output_dir = "/content/drive/MyDrive/Loras/fubuki_illus/output"
log_prefix = "fubuki_illus"
logging_dir = "/content/drive/MyDrive/Loras/_logs"
wandb_api_key = "ef4d900d0c1f0dcfc295578a23bda6fc5805b7e2"
log_with = "wandb"