[network_arguments]

unet_lr = 0.0003

text_encoder_lr = 6e-5

network_dim = 64

network_alpha = 64

network_module = "networks.lora"

network_args = [ "conv_dim=64", "conv_alpha=64",]

network_train_unet_only = false

[optimizer_arguments]

learning_rate = 0.0003

lr_scheduler = "cosine_with_restarts"

lr_scheduler_num_cycles = 3

lr_warmup_steps = 350

optimizer_type = "AdamW8bit"

optimizer_args = [ "weight_decay=0.1", "betas=[0.9,0.99]",]

[training_arguments]

pretrained_model_name_or_path = "uYouUs/IllustriousV01"

vae = "stabilityai/sdxl-vae"

max_train_steps = 7000

train_batch_size = 4

seed = 42

max_token_length = 225

xformers = false

sdpa = true

min_snr_gamma = 8.0

lowram = true

no_half_vae = true

gradient_checkpointing = true

gradient_accumulation_steps = 1

max_data_loader_n_workers = 3

persistent_data_loader_workers = true

mixed_precision = "fp16"

full_bf16 = false

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

v_parameterization = false

scale_v_pred_loss_like_noise_pred = false

zero_terminal_snr = false

[saving_arguments]

save_precision = "fp16"

save_model_as = "safetensors"

save_every_n_epochs = 1

save_last_n_epochs = 10

output_name = "64illu0lora"

output_dir = "/content/drive/MyDrive/Loras/example/output"

log_prefix = "64illu0lora"

logging_dir = "/content/Loras/_logs"

wandb_api_key = "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"

log_with = "wandb"