characters/kobato/auto_save_kobato.toml

[[subsets]]
num_repeats = 2
keep_tokens = 1
caption_extension = ".txt"
shuffle_caption = true
flip_aug = false
color_aug = false
random_crop = true
is_reg = false
image_dir = "F:/Pictures/grabber_stuff/k/keep"

[noise_args]

[sample_args]

[logging_args]

[general_args.args]
pretrained_model_name_or_path = "F:/Desktop/stable diffusion/LoRA/AnimeFullFinal.safetensors"
mixed_precision = "bf16"
seed = 23
clip_skip = 2
xformers = true
max_data_loader_n_workers = 1
persistent_data_loader_workers = true
max_token_length = 225
prior_loss_weight = 1.0
max_train_steps = 1600

[general_args.dataset_args]
resolution = 768
batch_size = 2

[network_args.args]
network_dim = 16
network_alpha = 8.0

[optimizer_args.args]
optimizer_type = "AdamW8bit"
lr_scheduler = "cosine_with_restarts"
learning_rate = 0.0005
warmup_ratio = 0.05
lr_scheduler_num_cycles = 2
text_encoder_lr = 0.0001

[saving_args.args]
output_dir = "E:/stable_diffusion_models_and_outputs/models/LyCORIS/v1/Characters/kobato"
save_precision = "fp16"
save_model_as = "safetensors"
output_name = "kobato"
save_every_n_epochs = 1
tag_occurrence = true
save_toml = true

[bucket_args.dataset_args]
enable_bucket = true
min_bucket_reso = 256
max_bucket_reso = 1024
bucket_reso_steps = 64

[network_args.args.network_args]
down_lr_weight = [ "1.0", "0.99", "0.96", "0.91", "0.84", "0.76", "0.65", "0.54", "0.42", "0.28", "0.14", "0.0",]
mid_lr_weight = 0.5
up_lr_weight = [ "0.0", "0.14", "0.28", "0.42", "0.54", "0.65", "0.76", "0.84", "0.91", "0.96", "0.99", "1.0",]
block_dims = [ "8", "7", "7", "7", "6", "6", "5", "4", "3", "2", "1", "0", "4", "8", "1", "2", "3", "4", "5", "6", "6", "7", "7", "7", "8",]

[optimizer_args.args.optimizer_args]
weight_decay = 0.1
betas = "0.9,0.99"