[network_arguments]unet_lr = 8e-5text_encoder_lr = 5e-5network_dim = 32network_alpha = 16network_module = "networks.lora"network_train_unet_only = false[optimizer_arguments]learning_rate = 8e-5lr_scheduler = "cosine_with_restarts"lr_scheduler_num_cycles = 3lr_warmup_steps = 17optimizer_type = "LoraEasyCustomOptimizer.came.CAME"optimizer_args = [ "weight_decay=0.04",]loss_type = "l2"max_grad_norm = 1.0[training_arguments]lowram = truepretrained_model_name_or_path = "/content/downloaded_model.safetensors"vae = "/content/sdxl_vae.safetensors"max_train_epochs = 8train_batch_size = 4seed = 42max_token_length = 225xformers = falsesdpa = trueno_half_vae = truegradient_checkpointing = truegradient_accumulation_steps = 1max_data_loader_n_workers = 1persistent_data_loader_workers = truemixed_precision = "fp16"full_fp16 = truefull_bf16 = falsecache_latents = truecache_latents_to_disk = truecache_text_encoder_outputs = falsemin_timestep = 0max_timestep = 1000prior_loss_weight = 1.0multires_noise_iterations = 6multires_noise_discount = 0.3v_parameterization = truescale_v_pred_loss_like_noise_pred = truezero_terminal_snr = true[saving_arguments]save_precision = "fp16"save_model_as = "safetensors"save_every_n_epochs = 1save_last_n_epochs = 8output_name = "anyillu"output_dir = "/content/drive/MyDrive/Loras/anyillu/output"log_prefix = "anyillu"logging_dir = "/content/drive/MyDrive/Loras/_logs"<h2></h2>

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