[model_arguments]
v2 = true
v_parameterization = true
pretrained_model_name_or_path = "/content/pretrained_model/Replicant-V3.0_fp16.safetensors"

[optimizer_arguments]
min_snr_gamma = 5
optimizer_type = "AdamW8bit"
learning_rate = 1e-6
max_grad_norm = 1.0
train_text_encoder = true
lr_scheduler = "constant"
lr_warmup_steps = 0

[dataset_arguments]
debug_dataset = false
in_json = "/content/fine_tune/config/meta_lat.json"
train_data_dir = "/content/fine_tune/train_data"
dataset_repeats = 1
shuffle_caption = true
keep_tokens = 0
resolution = "768,768"
caption_dropout_rate = 0
caption_tag_dropout_rate = 0
caption_dropout_every_n_epochs = 0
color_aug = false
token_warmup_min = 1
token_warmup_step = 0

[training_arguments]
output_dir = "/content/fine_tune/output"
output_name = "regainer-v0"
save_precision = "fp16"
save_n_epoch_ratio = 1
save_state = true
train_batch_size = 1
max_token_length = 225
mem_eff_attn = false
xformers = true
max_train_steps = 3640
max_data_loader_n_workers = 8
persistent_data_loader_workers = true
gradient_checkpointing = false
gradient_accumulation_steps = 1
mixed_precision = "fp16"
logging_dir = "/content/fine_tune/logs"
log_prefix = "regainer-v0"
noise_offset = 0.12

[sample_prompt_arguments]
sample_every_n_steps = 100
sample_sampler = "ddim"

[saving_arguments]
save_model_as = "safetensors"