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[sdxl_arguments] |
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cache_text_encoder_outputs = true |
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no_half_vae = true |
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min_timestep = 0 |
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max_timestep = 1000 |
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shuffle_caption = false |
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|
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[model_arguments] |
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pretrained_model_name_or_path = "/content/pretrained_model/sd_xl_base_0.9.safetensors" |
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vae = "/content/vae/sdxl_vae.safetensors" |
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|
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[dataset_arguments] |
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debug_dataset = false |
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in_json = "/content/fine_tune/meta_lat.json" |
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train_data_dir = "/content/fine_tune/train_data" |
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dataset_repeats = 1 |
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keep_tokens = 0 |
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resolution = "1024,1024" |
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caption_dropout_rate = 0 |
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caption_tag_dropout_rate = 0 |
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caption_dropout_every_n_epochs = 0 |
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color_aug = false |
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token_warmup_min = 1 |
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token_warmup_step = 0 |
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|
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[training_arguments] |
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output_dir = "/content/drive/MyDrive/kohya-trainer/output" |
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output_name = "sdxl_finetune" |
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save_precision = "fp16" |
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save_every_n_steps = 1000 |
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train_batch_size = 4 |
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max_token_length = 225 |
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mem_eff_attn = false |
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xformers = true |
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max_train_steps = 2500 |
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max_data_loader_n_workers = 8 |
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persistent_data_loader_workers = true |
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gradient_checkpointing = true |
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gradient_accumulation_steps = 1 |
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mixed_precision = "bf16" |
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|
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[logging_arguments] |
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log_with = "tensorboard" |
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logging_dir = "/content/fine_tune/logs" |
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log_prefix = "sdxl_finetune" |
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|
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[sample_prompt_arguments] |
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sample_every_n_steps = 100 |
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sample_sampler = "euler_a" |
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|
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[saving_arguments] |
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save_model_as = "safetensors" |
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|
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[optimizer_arguments] |
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optimizer_type = "AdaFactor" |
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learning_rate = 4e-7 |
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max_grad_norm = 1.0 |
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optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False",] |
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lr_scheduler = "constant_with_warmup" |
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lr_warmup_steps = 100 |
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|
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[advanced_training_config] |
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|