[[datasets]]

[[datasets.subsets]]
num_repeats = 3

[general]
resolution = 1024
shuffle_caption = true
keep_tokens = 3
flip_aug = true
enable_bucket = true
bucket_reso_steps = 64
bucket_no_upscale = true
min_bucket_reso = 256
max_bucket_reso = 2048

[additional_network_arguments]
unet_lr = 0.0005
text_encoder_lr = 5e-5
network_dim = 128
network_alpha = 16
network_module = "networks.lora"

[optimizer_arguments]
learning_rate = 0.0005
lr_scheduler = "cosine"
lr_warmup_steps = 0
optimizer_type = "Adafactor"
optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False",]

[training_arguments]
max_train_steps = 0
max_train_epochs = 52

sample_sampler = "euler_a"
train_batch_size = 5
noise_offset = 0.03
clip_skip = 2
weighted_captions = false
max_token_length = 225
lowram = false
max_data_loader_n_workers = 8
persistent_data_loader_workers = true
save_precision = "bf16"
mixed_precision = "bf16"
save_state = false
xformers = true
sdpa = true
no_half_vae = true
gradient_checkpointing = true
gradient_accumulation_steps = 1

[advanced_training_config]
multires_noise_iterations = 6
multires_noise_discount = 0.3
min_snr_gamma = 5.0

[model_arguments]
v2 = false

[dreambooth_arguments]
prior_loss_weight = 1.0

[dataset_arguments]
cache_latents = true