abarb_v1.json

{
  "LoRA_type": "Standard",
  "adaptive_noise_scale": 0.00357,
  "additional_parameters": "--log_prefix=xl-loha",
  "block_alphas": "",
  "block_dims": "",
  "block_lr_zero_threshold": "",
  "bucket_no_upscale": false,
  "bucket_reso_steps": 64,
  "cache_latents": true,
  "cache_latents_to_disk": true,
  "caption_dropout_every_n_epochs": 0.0,
  "caption_dropout_rate": 0,
  "caption_extension": ".txt2",
  "clip_skip": "1",
  "color_aug": false,
  "conv_alpha": 4,
  "conv_block_alphas": "",
  "conv_block_dims": "",
  "conv_dim": 4,
  "decompose_both": false,
  "dim_from_weights": false,
  "down_lr_weight": "",
  "enable_bucket": true,
  "epoch": 10,
  "factor": -1,
  "flip_aug": false,
  "full_bf16": false,
  "full_fp16": false,
  "gradient_accumulation_steps": 1,
  "gradient_checkpointing": false,
  "keep_tokens": 1,
  "learning_rate": 2e-05,
  "logging_dir": "/workspace/kohya_ss/dataset/kohya-training/log",
  "lora_network_weights": "",
  "lr_scheduler": "adafactor",
  "lr_scheduler_args": "",
  "lr_scheduler_num_cycles": "1",
  "lr_scheduler_power": "",
  "lr_warmup": 0,
  "max_bucket_reso": 2048,
  "max_data_loader_n_workers": "0",
  "max_resolution": "1024,1024",
  "max_timestep": 1000,
  "max_token_length": "75",
  "max_train_epochs": "",
  "max_train_steps": "",
  "mem_eff_attn": false,
  "mid_lr_weight": "",
  "min_bucket_reso": 64,
  "min_snr_gamma": 0,
  "min_timestep": 0,
  "mixed_precision": "bf16",
  "model_list": "custom",
  "module_dropout": 0,
  "multires_noise_discount": 0,
  "multires_noise_iterations": 0,
  "network_alpha": 8,
  "network_dim": 32,
  "network_dropout": 0,
  "no_token_padding": false,
  "noise_offset": 0.0357,
  "noise_offset_type": "Original",
  "num_cpu_threads_per_process": 16,
  "optimizer": "Adafactor",
  "optimizer_args": "",
  "output_dir": "/workspace/kohya_ss/dataset/kohya-training/model",
  "output_name": "abarb_v1",
  "persistent_data_loader_workers": false,
  "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0",
  "prior_loss_weight": 1.0,
  "random_crop": false,
  "rank_dropout": 0,
  "reg_data_dir": "/workspace/kohya_ss/dataset/kohya-training/reg",
  "resume": "",
  "sample_every_n_epochs": 0,
  "sample_every_n_steps": 250,
  "sample_prompts": "a photo \\(medium\\) of abarb \\(subject\\), smile, highres, best quality, full sharp, 4 k photography --n lowres, low quality, blurry, out of focus, low effort, poor --w 1024 --h 1024 --d 420 --l 7.5 --s 30\n\na photo \\(medium\\) of abarb \\(subject\\), upper body, highres, best quality, full sharp, 4 k photography --n lowres, low quality, blurry, out of focus, low effort, poor --w 832 --h 1216 --d 421 --l 7.5 --s 30\n\na photo \\(medium\\) of abarb \\(subject\\), smile, highres, best quality, full sharp, 4 k photography --n lowres, low quality, blurry, out of focus, low effort, poor --w 1152 --h 896 --d 422 --l 7.5 --s 30\n\na photo \\(medium\\) of abarb \\(subject\\), swimsuit \\(wardrobe\\), highres, best quality, full sharp, 4 k photography --n lowres, low quality, blurry, out of focus, low effort, poor --w 896 --h 1152 --d 423 --l 7.5 --s 30",
  "sample_sampler": "euler_a",
  "save_every_n_epochs": 1,
  "save_every_n_steps": 0,
  "save_last_n_steps": 0,
  "save_last_n_steps_state": 0,
  "save_model_as": "safetensors",
  "save_precision": "bf16",
  "save_state": true,
  "scale_v_pred_loss_like_noise_pred": false,
  "scale_weight_norms": 1,
  "sdxl": true,
  "sdxl_cache_text_encoder_outputs": false,
  "sdxl_no_half_vae": true,
  "seed": "",
  "shuffle_caption": false,
  "stop_text_encoder_training": 0,
  "text_encoder_lr": 2e-05,
  "train_batch_size": 1,
  "train_data_dir": "/workspace/kohya_ss/dataset/kohya-training/img",
  "train_on_input": false,
  "training_comment": "trigger: the white queen",
  "unet_lr": 2e-05,
  "unit": 1,
  "up_lr_weight": "",
  "use_cp": false,
  "use_wandb": true,
  "v2": false,
  "v_parameterization": false,
  "v_pred_like_loss": 0,
  "vae_batch_size": 0,
  "wandb_api_key": "0c90f14969d47b1b86b7fe4f2ecca630f3540eb6",
  "weighted_captions": false,
  "xformers": "xformers"
}