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