bucket_no_upscale = true
bucket_reso_steps = 64
cache_latents = true
cache_latents_to_disk = true
caption_extension = ".txt"
clip_skip = 1
dynamo_backend = "no"
enable_bucket = true
epoch = 1
gradient_accumulation_steps = 1
gradient_checkpointing = true
huber_c = 0.1
huber_schedule = "snr"
learning_rate = 1.0
logging_dir = "/workspace/SL-DATASET/log"
loss_type = "l2"
lr_scheduler = "cosine"
lr_scheduler_args = []
lr_scheduler_num_cycles = 1
lr_scheduler_power = 1
max_bucket_reso = 2048
max_data_loader_n_workers = 0
max_grad_norm = 1
max_timestep = 1000
max_token_length = 75
max_train_steps = 1600
metadata_author = "m1nd3xpand3r"
metadata_description = "Just a few test to see how it looks for better train"
metadata_title = "st3phl0v3-selfie"
min_bucket_reso = 256
mixed_precision = "fp16"
multires_noise_discount = 0.2
multires_noise_iterations = 8
network_alpha = 32
network_args = []
network_dim = 32
network_module = "networks.lora"
no_half_vae = true
noise_offset = 0.0357
noise_offset_type = "Original"
optimizer_args = [ "decouple=True", "weight_decay=0.5", "betas=0.9,0.99", "use_bias_correction=False",]
optimizer_type = "Prodigy"
output_dir = "/workspace/SL-DATASET/model"
output_name = "last"
pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0"
prior_loss_weight = 1
resolution = "1024,1024"
sample_prompts = "/workspace/SL-DATASET/model/prompt.txt"
sample_sampler = "euler_a"
save_every_n_epochs = 1
save_model_as = "safetensors"
save_precision = "fp16"
scale_weight_norms = 1
seed = 12345
text_encoder_lr = 1
train_batch_size = 4
train_data_dir = "/workspace/SL-DATASET/img"
unet_lr = 1
xformers = true