| bucket_no_upscale = true | |
| bucket_reso_steps = 64 | |
| cache_latents = true | |
| cache_latents_to_disk = true | |
| clip_skip = 1 | |
| dynamo_backend = "no" | |
| epoch = 1 | |
| full_fp16 = true | |
| gradient_accumulation_steps = 1 | |
| gradient_checkpointing = true | |
| huber_c = 0.1 | |
| huber_schedule = "snr" | |
| learning_rate = 1e-5 | |
| learning_rate_te1 = 3e-6 | |
| logging_dir = "/kaggle/working/outputs/log" | |
| loss_type = "l2" | |
| lr_scheduler = "constant" | |
| lr_scheduler_args = [] | |
| lr_scheduler_num_cycles = 1 | |
| lr_scheduler_power = 1 | |
| max_bucket_reso = 2048 | |
| max_data_loader_n_workers = 0 | |
| max_timestep = 1000 | |
| max_token_length = 75 | |
| max_train_steps = 800 | |
| min_bucket_reso = 256 | |
| mixed_precision = "fp16" | |
| noise_offset_type = "Original" | |
| optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False", "weight_decay=0.01",] | |
| optimizer_type = "Adafactor" | |
| output_dir = "/kaggle/temp/models" | |
| output_name = "Kaggle_SDXL_Base_DreamBooth" | |
| pretrained_model_name_or_path = "stabilityai/stable-diffusion-xl-base-1.0" | |
| prior_loss_weight = 1 | |
| reg_data_dir = "/kaggle/working/outputs/reg" | |
| resolution = "1024,1024" | |
| sample_prompts = "/kaggle/temp/models/prompt.txt" | |
| sample_sampler = "euler_a" | |
| save_every_n_epochs = 1 | |
| save_every_n_steps = 2251 | |
| save_model_as = "safetensors" | |
| save_precision = "fp16" | |
| train_batch_size = 2 | |
| train_data_dir = "/kaggle/working/outputs/img" | |
| vae = "stabilityai/sdxl-vae" | |
| vae_batch_size = 4 | |
| xformers = true | |