auto_save_mokopekkotest3.toml

[[subsets]]
num_repeats = 10
caption_extension = ".txt"
shuffle_caption = false
flip_aug = false
is_reg = false
image_dir = "E:/Everything artificial intelligence/loradataset\\10_ohw mokopekko"
keep_tokens = 0

[sample_args]

[logging_args]

[general_args.args]
pretrained_model_name_or_path = "E:/Everything artificial intelligence/stable-diffusion-webui/models/Stable-diffusion/animefull-final-pruned-fp16.safetensors"
mixed_precision = "fp16"
seed = 23
max_data_loader_n_workers = 1
persistent_data_loader_workers = true
max_token_length = 225
prior_loss_weight = 1.0
vae = ""
max_train_epochs = 30
clip_skip = 2
xformers = true
cache_latents = true
gradient_checkpointing = true
gradient_accumulation_steps = 1

[general_args.dataset_args]
resolution = 896
batch_size = 8

[network_args.args]
network_dim = 4
network_alpha = 1.0
min_timestep = 0
max_timestep = 1000
network_dropout = 0.5

[optimizer_args.args]
optimizer_type = "AdamW8bit"
lr_scheduler = "cosine"
learning_rate = 0.0001
max_grad_norm = 1.0
lr_scheduler_type = "LoraEasyCustomOptimizer.CustomOptimizers.CosineAnnealingWarmupRestarts"
lr_scheduler_num_cycles = 4
unet_lr = 0.0005
warmup_ratio = 0.1
min_snr_gamma = 8
scale_weight_norms = 5.0

[saving_args.args]
output_dir = "E:/Everything artificial intelligence/stable-diffusion-webui/models/Lora"
save_precision = "fp16"
save_model_as = "safetensors"
output_name = "mokopekkotest3"
tag_occurrence = true
save_toml = true
save_every_n_epochs = 2

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

[noise_args.args]
multires_noise_iterations = 6
multires_noise_discount = 0.3

[network_args.args.network_args]
conv_dim = 16
conv_alpha = 8.0
module_dropout = 0.25

[optimizer_args.args.lr_scheduler_args]
min_lr = 1e-6
gamma = 0.85

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