[model_arguments] | |
v2 = true | |
v_parameterization = true | |
pretrained_model_name_or_path = "/content/drive/MyDrive/pretrained_model/Anything-v3-1.safetensors" | |
[additional_network_arguments] | |
no_metadata = false | |
unet_lr = 0.0001 | |
text_encoder_lr = 5e-5 | |
network_module = "networks.lora" | |
network_dim = 64 | |
network_alpha = 32 | |
network_train_unet_only = false | |
network_train_text_encoder_only = false | |
[optimizer_arguments] | |
optimizer_type = "AdamW" | |
learning_rate = 0.0001 | |
max_grad_norm = 1.0 | |
lr_scheduler = "constant" | |
lr_warmup_steps = 0 | |
[dataset_arguments] | |
cache_latents = true | |
debug_dataset = false | |
[training_arguments] | |
output_dir = "/content/drive/MyDrive/LoRA/output" | |
output_name = "kohya" | |
save_precision = "fp16" | |
save_every_n_epochs = 1 | |
train_batch_size = 6 | |
max_token_length = 225 | |
mem_eff_attn = false | |
xformers = true | |
max_train_epochs = 10 | |
max_data_loader_n_workers = 8 | |
persistent_data_loader_workers = true | |
gradient_checkpointing = false | |
gradient_accumulation_steps = 1 | |
mixed_precision = "fp16" | |
logging_dir = "/content/LoRA/logs" | |
log_prefix = "kohya" | |
lowram = false | |
[sample_prompt_arguments] | |
sample_every_n_epochs = 1 | |
sample_sampler = "euler_a" | |
[dreambooth_arguments] | |
prior_loss_weight = 1.0 | |
[saving_arguments] | |
save_model_as = "safetensors" | |