滴滴 v001

命令行设置

• accelerate.EXE launch --dynamo_backend no --dynamo_mode default --mixed_precision bf16 --num_processes 2 --num_machines 1 --num_cpu_threads_per_process 2

• sdxl_train_network.py --config_file config_lora-20240618-184456.toml

• --lr_scheduler_type CosineAnnealingLR

• --lr_scheduler_args T_max=1040 eta_min=1e-7

• --network_args loraplus_lr_ratio=16

• --alpha_mask

toml 配置文件

• bucket_no_upscale = true

• bucket_reso_steps = 64

• cache_latents = true

• cache_latents_to_disk = true

• caption_dropout_rate = 0.05

• caption_extension = ".txt"

• clip_skip = 1

• dynamo_backend = "no"

• enable_bucket = true

• epoch = 100

• gradient_accumulation_steps = 1

• gradient_checkpointing = true

• huber_c = 0.1

• huber_schedule = "snr"

• keep_tokens = 1

• learning_rate = 0.0001

• log_with = "wandb"

• logging_dir = "log"

• loss_type = "smooth_l1"

• lr_scheduler = "cosine"

• lr_scheduler_args = []

• lr_scheduler_num_cycles = 1

• lr_scheduler_power = 1

• max_bucket_reso = 2048

• max_data_loader_n_workers = 0

• max_grad_norm = 0.1

• max_timestep = 1000

• max_token_length = 225

• max_train_epochs = 100

• max_train_steps = 10400

• mem_eff_attn = true

• min_bucket_reso = 256

• min_snr_gamma = 5

• mixed_precision = "bf16"

• network_alpha = 32

• network_args = ["rank_dropout=0.2", "module_dropout=0.2"]

• network_dim = 32

• network_dropout = 0.2

• network_module = "networks.lora"

• no_half_vae = true

• noise_offset_type = "Original"

• optimizer_args = ["weight_decay=0.01"]

• optimizer_type = "AdamW8bit"

• output_dir = "output"

• output_name = "intravenousdrip-XLPony_001"

• pretrained_model_name_or_path = "ponyDiffusionV6XL_v6StartWithThisOne.safetensors"

• prior_loss_weight = 0.1

• resolution = "1024,1024"

• sample_prompts = "prompt.txt"

• sample_sampler = "euler_a"

• save_every_n_epochs = 10

• save_model_as = "safetensors"

• save_precision = "bf16"

• save_state = true

• seed = 1

• shuffle_caption = true

• text_encoder_lr = 1e-5

• train_batch_size = 1

• unet_lr = 0.0001

• xformers = true