To create a public link, set `share=True` in `launch()`.
Loading config...
Save...
Folder 10_loonanudes furry: 960 steps
Folder 14_tsampikos furry: 1022 steps
Folder 17_jay-naylor furry: 1003 steps
Folder 18_fluff-kevlar furry: 990 steps
Folder 18_slugbox furry: 990 steps
max_train_steps = 1242
stop_text_encoder_training = 0
lr_warmup_steps = 124
accelerate launch --num_cpu_threads_per_process=32 "train_network.py" --enable_bucket --pretrained_model_name_or_path="F:/stable-diffusion/models/Stable-diffusion/AbyssOrangeMix_base.ckpt" --train_data_dir="F:/kohya_ss/model/testdata-prep-test/img" --resolution=512,512 --output_dir="F:/kohya_ss/model/testdata-prep-test/model" --logging_dir="F:/kohya_ss/model/testdata-prep-test/log" --prior_loss_weight=0.0 --network_module=networks.lora --text_encoder_lr=5e-5 --unet_lr=1e-3 --network_dim=128 --output_name="baseorange_furlsut_lora-fix" --learning_rate="1e-4" --lr_scheduler="cosine" --lr_warmup_steps="124" --train_batch_size="4" --max_train_steps="1242" --save_every_n_epochs="1" --mixed_precision="fp16" --save_precision="fp16" --seed="228228" --caption_extension=".txt" --cache_latents --max_train_epochs="10" --max_token_length=225 --clip_skip=2 --flip_aug --xformers
prepare tokenizer
update token length: 225
Use DreamBooth method.
prepare train images.
found directory 10_loonanudes furry contains 96 image files
found directory 14_tsampikos furry contains 73 image files
found directory 17_jay-naylor furry contains 59 image files
found directory 18_fluff-kevlar furry contains 55 image files
found directory 18_slugbox furry contains 55 image files
4965 train images with repeating.
loading image sizes.
100%|██████████████████████████████████████████████████████| 338/338 [00:00<00:00, 1511.00it/s]
make buckets
number of images (including repeats) / 各bucketの画像枚数（繰り返し回数を含む）
bucket 0: resolution (256, 832), count: 0
bucket 1: resolution (256, 896), count: 0
bucket 2: resolution (256, 960), count: 0
bucket 3: resolution (256, 1024), count: 0
bucket 4: resolution (320, 704), count: 0
bucket 5: resolution (320, 768), count: 0
bucket 6: resolution (384, 640), count: 0
bucket 7: resolution (448, 576), count: 0
bucket 8: resolution (512, 512), count: 4965
bucket 9: resolution (576, 448), count: 0
bucket 10: resolution (640, 384), count: 0
bucket 11: resolution (704, 320), count: 0
bucket 12: resolution (768, 320), count: 0
bucket 13: resolution (832, 256), count: 0
bucket 14: resolution (896, 256), count: 0
bucket 15: resolution (960, 256), count: 0
bucket 16: resolution (1024, 256), count: 0
mean ar error (without repeats): 0.0
prepare accelerator
Using accelerator 0.15.0 or above.
load StableDiffusion checkpoint
loading u-net: <All keys matched successfully>
loading vae: <All keys matched successfully>
Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPTextModel: ['vision_model.embeddings.position_embedding.weight', 'vision_model.encoder.layers.18.mlp.fc1.bias', 'vision_model.encoder.layers.12.layer_norm2.bias', 'vision_model.encoder.layers.11.self_attn.out_proj.weight', 'vision_model.encoder.layers.2.self_attn.v_proj.weight', 'vision_model.encoder.layers.17.layer_norm1.bias', 'vision_model.encoder.layers.0.self_attn.q_proj.bias', 'vision_model.encoder.layers.19.self_attn.v_proj.bias', 'vision_model.encoder.layers.0.layer_norm1.bias', 'vision_model.encoder.layers.11.layer_norm2.bias', 'vision_model.encoder.layers.19.layer_norm2.bias', 'vision_model.encoder.layers.8.mlp.fc2.bias', 'vision_model.encoder.layers.12.mlp.fc2.bias', 'vision_model.encoder.layers.16.self_attn.q_proj.weight', 'vision_model.encoder.layers.6.self_attn.q_proj.weight', 'vision_model.encoder.layers.23.mlp.fc1.weight', 'vision_model.encoder.layers.13.mlp.fc2.bias', 'vision_model.encoder.layers.1.layer_norm2.bias', 'vision_model.encoder.layers.20.layer_norm1.weight', 'vision_model.encoder.layers.22.mlp.fc2.weight', 'vision_model.encoder.layers.17.layer_norm2.weight', 'vision_model.encoder.layers.15.self_attn.v_proj.bias', 'vision_model.encoder.layers.13.self_attn.k_proj.weight', 'vision_model.encoder.layers.11.layer_norm2.weight', 'vision_model.encoder.layers.20.layer_norm1.bias', 'vision_model.encoder.layers.3.self_attn.q_proj.bias', 'vision_model.encoder.layers.0.self_attn.k_proj.bias', 'vision_model.encoder.layers.15.self_attn.q_proj.weight', 'vision_model.encoder.layers.9.self_attn.v_proj.weight', 'vision_model.encoder.layers.14.layer_norm2.bias', 'vision_model.encoder.layers.4.layer_norm1.bias', 'text_projection.weight', 'vision_model.encoder.layers.16.layer_norm2.bias', 'vision_model.encoder.layers.2.self_attn.out_proj.weight', 'vision_model.encoder.layers.16.self_attn.v_proj.bias', 'vision_model.encoder.layers.11.mlp.fc1.bias', 'vision_model.encoder.layers.10.self_attn.k_proj.weight', 'vision_model.encoder.layers.13.mlp.fc2.weight', 'vision_model.encoder.layers.3.layer_norm1.weight', 'vision_model.encoder.layers.10.self_attn.v_proj.weight', 'vision_model.encoder.layers.22.layer_norm1.weight', 'vision_model.encoder.layers.3.self_attn.k_proj.weight', 'vision_model.encoder.layers.12.self_attn.v_proj.weight', 'vision_model.encoder.layers.8.self_attn.q_proj.bias', 'vision_model.encoder.layers.18.layer_norm2.bias', 'vision_model.encoder.layers.21.layer_norm1.bias', 'vision_model.encoder.layers.0.layer_norm2.bias', 'vision_model.encoder.layers.16.self_attn.k_proj.bias', 'vision_model.encoder.layers.21.self_attn.v_proj.bias', 'vision_model.encoder.layers.12.self_attn.out_proj.bias', 'vision_model.encoder.layers.20.self_attn.v_proj.weight', 'vision_model.encoder.layers.6.mlp.fc1.bias', 'vision_model.encoder.layers.20.mlp.fc1.bias', 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'vision_model.encoder.layers.23.self_attn.v_proj.weight', 'vision_model.encoder.layers.7.layer_norm1.bias', 'vision_model.encoder.layers.20.self_attn.v_proj.bias', 'vision_model.encoder.layers.2.layer_norm1.bias', 'vision_model.encoder.layers.9.self_attn.out_proj.bias', 'vision_model.encoder.layers.22.mlp.fc1.bias', 'vision_model.encoder.layers.6.self_attn.q_proj.bias', 'vision_model.encoder.layers.0.self_attn.v_proj.weight', 'vision_model.encoder.layers.7.layer_norm1.weight', 'vision_model.encoder.layers.22.self_attn.out_proj.bias', 'vision_model.encoder.layers.18.mlp.fc1.weight', 'vision_model.encoder.layers.13.mlp.fc1.weight', 'vision_model.encoder.layers.6.layer_norm2.bias', 'vision_model.encoder.layers.20.self_attn.k_proj.bias', 'vision_model.encoder.layers.6.mlp.fc2.bias', 'vision_model.encoder.layers.10.mlp.fc2.bias', 'vision_model.encoder.layers.2.layer_norm1.weight', 'vision_model.encoder.layers.15.self_attn.k_proj.bias', 'vision_model.encoder.layers.17.mlp.fc1.weight', 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- This IS expected if you are initializing CLIPTextModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing CLIPTextModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).