pretrained_model_name_or_path = "C:\\sd\\webui\\models\\Stable-diffusion\\animagine-xl-3.0.safetensors" train_data_dir = "C:\\sd\\sd-scripts\\resource\\popularity_contest\\gakushu" shuffle_caption = true caption_extension = ".txt" keep_tokens = 1 resolution = "1024,1024" cache_latents = true enable_bucket = true min_bucket_reso = 512 max_bucket_reso = 2048 in_json = "C:\\sd\\sd-scripts\\resource\\popularity_contest\\marge_clean.json" dataset_repeats = 13 output_dir = "C:\\sd\\webui\\models\\Lora" output_name = "popularity_contest_v1_sdxl" save_precision = "fp16" save_every_n_epochs = 1 train_batch_size = 12 max_token_length = 225 xformers = true max_train_epochs = 6 max_data_loader_n_workers = 4 persistent_data_loader_workers = true seed = 23 mixed_precision = "fp16" logging_dir = "logs" learning_rate = 0.0001 lr_scheduler = "cosine_with_restarts" lr_warmup_steps = 100 lr_scheduler_num_cycles = 4 unet_lr = 0.0001 text_encoder_lr = 5e-5 network_module = "networks.lora" network_dim = 32 network_alpha = 16 gradient_checkpointing = true optimizer_type = "AdamW8bit" debiased_estimation_loss =true