bucket_no_upscale = true

bucket_reso_steps = 64

cache_latents = true

caption_dropout_rate = 0.12

caption_extension = ".txt"

clip_skip = 2

dynamo_backend = "no"

enable_bucket = true

epoch = 7

gradient_accumulation_steps = 1

gradient_checkpointing = true

huber_c = 0.1

huber_scale = 1

huber_schedule = "snr"

learning_rate = 0.0001

loraplus_lr_ratio = 16

loraplus_text_encoder_lr_ratio = 16

loraplus_unet_lr_ratio = 16

loss_type = "l2"

lr_scheduler = "cosine_with_restarts"

lr_scheduler_args = []

lr_scheduler_num_cycles = 3

lr_scheduler_power = 1

lr_warmup_steps = 0.05

max_bucket_reso = 3072

max_data_loader_n_workers = 2

max_grad_norm = 1

max_timestep = 1000

max_token_length = 150

max_train_steps = 3633

min_bucket_reso = 768

min_snr_gamma = 5

mixed_precision = "fp16"

network_alpha = 16

network_args = [ "rank_dropout=0.05", "module_dropout=0.05",]

network_dim = 32

network_dropout = 0.1

network_module = "networks.lora"

no_half_vae = true

noise_offset = 0.1

noise_offset_type = "Original"

optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False",]

optimizer_type = "Adafactor"

output_name = "SaltyXodium V1.3"

pretrained_model_name_or_path = "illustriousXL10_v10.safetensors"

prior_loss_weight = 1

resolution = "1280,1280"

sample_sampler = "euler_a"

save_model_as = "safetensors"

save_precision = "fp16"

shuffle_caption = true

skip_cache_check = true

text_encoder_lr = [ 5e-5, 5e-5,]

train_batch_size = 5

unet_lr = 0.0002

wandb_run_name = "SaltyXodium V1.3"

xformers = true