[model_arguments]
v2 = false
v_parameterization = false
pretrained_model_name_or_path = "/content/pretrained_model/AnyLoRA_noVae_fp16-pruned.ckpt"

[additional_network_arguments]
no_metadata = false
unet_lr = 0.0001
text_encoder_lr = 5e-5
network_module = "networks.lora"
network_dim = 16
network_alpha = 8
network_args = [ "conv_dim=8", "conv_alpha=1",]
network_train_unet_only = false
network_train_text_encoder_only = false

[optimizer_arguments]
min_snr_gamma = 5.0
optimizer_type = "AdamW8bit"
learning_rate = 0.0001
max_grad_norm = 1.0
optimizer_args = []
lr_scheduler = "constant_with_warmup"
lr_warmup_steps = 135

[dataset_arguments]
cache_latents = true
cache_latents_to_disk = true
debug_dataset = false
vae_batch_size = 4

[training_arguments]
output_dir = "/content/LoRA/output"
output_name = "simplevectorV2"
save_precision = "fp16"
save_every_n_epochs = 1
train_batch_size = 2
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_accumulation_steps = 1
mixed_precision = "fp16"
clip_skip = 2
lowram = true

[logging_arguments]
log_with = "tensorboard"
logging_dir = "/content/LoRA/logs"
log_prefix = "simplevectorV2"

[sample_prompt_arguments]
sample_every_n_epochs = 1
sample_sampler = "k_dpm_2_a"

[dreambooth_arguments]
prior_loss_weight = 1.0

[saving_arguments]
save_model_as = "safetensors"