|
[sdxl_arguments] |
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cache_text_encoder_outputs = false |
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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 = true |
|
lowram = true |
|
|
|
[model_arguments] |
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pretrained_model_name_or_path = "cagliostrolab/animagine-xl-3.0" |
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vae = "/content/vae/sdxl_vae.safetensors" |
|
|
|
[dataset_arguments] |
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debug_dataset = false |
|
in_json = "/content/LoRA/meta_lat.json" |
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train_data_dir = "/content/LoRA/train_data" |
|
dataset_repeats = 1 |
|
keep_tokens = 0 |
|
resolution = "1024,1024" |
|
color_aug = false |
|
token_warmup_min = 1 |
|
token_warmup_step = 0 |
|
|
|
[training_arguments] |
|
output_dir = "/content/drive/MyDrive/kohya-trainer/output/mee_japan_xl" |
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output_name = "mee_japan_xl" |
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save_precision = "fp16" |
|
save_every_n_epochs = 1 |
|
train_batch_size = 4 |
|
max_token_length = 225 |
|
mem_eff_attn = false |
|
sdpa = true |
|
xformers = false |
|
max_train_epochs = 10 |
|
max_data_loader_n_workers = 8 |
|
persistent_data_loader_workers = true |
|
gradient_checkpointing = true |
|
gradient_accumulation_steps = 1 |
|
mixed_precision = "fp16" |
|
|
|
[logging_arguments] |
|
log_with = "wandb" |
|
log_tracker_name = "mee_japan_xl" |
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logging_dir = "/content/LoRA/logs" |
|
|
|
[sample_prompt_arguments] |
|
sample_every_n_epochs = 1 |
|
sample_sampler = "euler_a" |
|
|
|
[saving_arguments] |
|
save_model_as = "safetensors" |
|
|
|
[optimizer_arguments] |
|
optimizer_type = "AdaFactor" |
|
learning_rate = 0.0001 |
|
max_grad_norm = 0 |
|
optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False",] |
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lr_scheduler = "constant_with_warmup" |
|
lr_warmup_steps = 100 |
|
|
|
[additional_network_arguments] |
|
no_metadata = false |
|
network_module = "networks.lora" |
|
network_dim = 32 |
|
network_alpha = 16 |
|
network_args = [] |
|
network_train_unet_only = true |
|
|