/vt/ - Virtual Youtubers

>>90352448
Here, I don't change much from default:
bucket_no_upscale = true
bucket_reso_steps = 64
cache_latents = true
clip_skip = 2
dynamo_backend = "no"
enable_bucket = true
epoch = 9
gradient_accumulation_steps = 1
gradient_checkpointing = true
huber_c = 0.1
huber_schedule = "snr"
learning_rate = 0.0004
loss_type = "l2"
lr_scheduler = "cosine"
lr_scheduler_args = []
lr_scheduler_num_cycles = 1
lr_scheduler_power = 1
lr_warmup_steps = 182
max_bucket_reso = 2048
max_data_loader_n_workers = 0
max_grad_norm = 1
max_timestep = 1000
max_token_length = 225
max_train_epochs = 9
max_train_steps = 1820
min_bucket_reso = 256
mixed_precision = "fp16"
multires_noise_discount = 0.3
network_alpha = 4
network_args = []
network_dim = 8
network_module = "networks.lora"
noise_offset_type = "Original"
optimizer_args = []
optimizer_type = "AdamW8bit"
pretrained_model_name_or_path = illustriousXL_smoothftSOLID.safetensors"
prior_loss_weight = 1
resolution = "1024,1024"
sample_sampler = "euler_a"
save_every_n_epochs = 1
save_model_as = "safetensors"
save_precision = "fp16"
text_encoder_lr = 0.0004
train_batch_size = 2
unet_lr = 0.0004
xformers = true