/kohya_ss/kohya_ss/kohya_gui/common_gui.py:1214: SyntaxWarning: invalid escape sequence '\i'
  "Please follow the folder structure documentation found at docs\image_folder_structure.md ..."
/kohya_ss/kohya_ss/kohya_gui/common_gui.py:1248: SyntaxWarning: invalid escape sequence '\i'
  f"...please follow the folder structure documentation found at docs\image_folder_structure.md ..."
/kohya_ss/kohya_ss/kohya_gui/common_gui.py:1258: SyntaxWarning: invalid escape sequence '\i'
  "Please follow the folder structure documentation found at docs\image_folder_structure.md ..."
/kohya_ss/kohya_ss/kohya_gui/wd14_caption_gui.py:242: SyntaxWarning: invalid escape sequence '\`'
  info="tag replacement in the format of `source1,target1;source2,target2; ...`. Escape `,` and `;` with `\`. e.g. `tag1,tag2;tag3,tag4`",
23:03:18-493653 INFO     Kohya_ss GUI version: v25.2.1                          
                                                                                
23:03:18-540884 INFO     Submodule initialized and updated.                     
23:03:18-541709 INFO     nVidia toolkit detected                                
23:03:19-823869 INFO     Torch 2.7.1+cu118                                      
23:03:20-117529 INFO     Torch backend: nVidia CUDA 11.8 cuDNN 90100            
23:03:20-150905 INFO     Torch detected GPU: NVIDIA H100 80GB HBM3 VRAM 81090MB 
                         Arch 9.0 Cores 132                                     
23:03:20-151825 INFO     Python version is 3.12.3 (main, Jun 18 2025, 17:59:45) 
                         [GCC 13.3.0]                                           
23:03:20-152659 INFO     Installing/Validating requirements from                
                         requirements_pytorch_windows.txt...                    
23:03:20-154062 INFO     Using uv for pip...                                    
23:03:20-238241 ERROR    Failed to install requirements from                    
                         requirements_pytorch_windows.txt. Pip command: 'uv pip 
                         install -r requirements_pytorch_windows.txt'. Exit     
                         code: 2                                                
23:03:20-239065 ERROR    Pip stderr: error: No virtual environment
                         found; run `uv venv` to create an environment, 
                         or pass `--system` to install into a           
                         non-virtual environment                                
23:03:20-240015 ERROR    Please check the requirements file path, your internet 
                         connection, and ensure pip is functioning correctly.   
23:03:20-535300 INFO     headless: False                                        
23:03:20-538722 INFO     Using shell=True when running external commands...     
* Running on local URL:  http://0.0.0.0:7860
* Running on public URL: https://903bc0cf19c7e560df.gradio.live

This share link expires in 1 week. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)
23:05:28-356733 INFO     Copy                                                   
                         /kaggle/working/kohya_ss/dataset/sreeleela14/images to 
                         /kaggle/working/kohya_ss/training_data/img/1_ohxw      
                         woman...                                               
23:05:28-369518 INFO     Regularization images directory is missing... not      
                         copying regularisation images...                       
23:05:28-372617 INFO     Done creating kohya_ss training folder structure at    
                         /kaggle/working/kohya_ss/training_data...              
23:05:35-037284 INFO     Removing existing directory                            
                         /kaggle/working/kohya_ss/training_data/img/1_ohxw      
                         woman...                                               
23:05:35-041887 INFO     Copy                                                   
                         /kaggle/working/kohya_ss/dataset/sreeleela14/images to 
                         /kaggle/working/kohya_ss/training_data/img/1_ohxw      
                         woman...                                               
23:05:35-055220 INFO     Regularization images directory is missing... not      
                         copying regularisation images...                       
23:05:35-058036 INFO     Done creating kohya_ss training folder structure at    
                         /kaggle/working/kohya_ss/training_data...              
23:06:11-954936 INFO     Copy                                                   
                         /kaggle/working/kohya_ss/dataset/sreeleela14/images to 
                         /kaggle/working/kohya_ss/training_data/img/1_ohwx      
                         woman...                                               
23:06:11-965543 INFO     Regularization images directory is missing... not      
                         copying regularisation images...                       
23:06:11-968299 INFO     Done creating kohya_ss training folder structure at    
                         /kaggle/working/kohya_ss/training_data...              
23:07:00-032675 INFO     Removing existing directory                            
                         /kaggle/working/kohya_ss/training_data/img/1_ohwx      
                         woman...                                               
23:07:00-037192 INFO     Copy                                                   
                         /kaggle/working/kohya_ss/dataset/sreeleela14/images to 
                         /kaggle/working/kohya_ss/training_data/img/1_ohwx      
                         woman...                                               
23:07:00-047526 INFO     Regularization images directory is missing... not      
                         copying regularisation images...                       
23:07:00-050531 INFO     Done creating kohya_ss training folder structure at    
                         /kaggle/working/kohya_ss/training_data...              
23:07:47-101988 INFO     Copy                                                   
                         /kaggle/working/kohya_ss/dataset/sreeleela14/images to 
                         /kaggle/working/kohya_ss/training_data/img/1_ohwx      
                         woman...                                               
23:07:47-115127 INFO     Regularization images directory is missing... not      
                         copying regularisation images...                       
23:07:47-117970 INFO     Done creating kohya_ss training folder structure at    
                         /kaggle/working/kohya_ss/training_data...              
23:10:50-645022 INFO     Start training Dreambooth...                           
23:10:50-647638 INFO     Validating lr scheduler arguments...                   
23:10:50-650177 INFO     Validating optimizer arguments...                      
23:10:50-652317 INFO     Validating /kaggle/working/kohya_ss/training_data/log  
                         existence and writability... SUCCESS                   
23:10:50-654695 INFO     Validating /kaggle/working/kohya_ss/training_data/model
                         existence and writability... SUCCESS                   
23:10:50-657460 INFO     Validating                                             
                         /kaggle/working/kohya_ss/flux1-dev.safetensors         
                         existence... SUCCESS                                   
23:10:50-659916 INFO     Validating /kaggle/working/kohya_ss/training_data/img  
                         existence... SUCCESS                                   
23:10:50-662494 INFO     Error: '.ipynb_checkpoints' does not contain an        
                         underscore, skipping...                                
23:10:50-664814 INFO     Folder 1_ohwx woman: 1 repeats found                   
23:10:50-666898 INFO     Folder 1_ohwx woman: 10 images found                   
23:10:50-669102 INFO     Folder 1_ohwx woman: 10 * 1 = 10 steps                 
23:10:50-671228 INFO     Regularization factor: 1                               
23:10:50-673121 INFO     Total steps: 10                                        
23:10:50-675116 INFO     Train batch size: 1                                    
23:10:50-677046 INFO     Gradient accumulation steps: 1                         
23:10:50-678934 INFO     Epoch: 200                                             
23:10:50-680952 INFO     max_train_steps (10 / 1 / 1 * 200 * 1) = 2000          
23:10:50-685485 INFO     lr_warmup_steps = 0                                    
23:10:50-691115 INFO     Saving training config to                              
                         /kaggle/working/kohya_ss/training_data/model/anupama_20
                         250708-231050.json...                                  
23:10:50-694977 INFO     Executing command: /usr/local/bin/accelerate launch    
                         --dynamo_backend no --dynamo_mode default              
                         --mixed_precision bf16 --num_processes 1 --num_machines
                         1 --num_cpu_threads_per_process 2                      
                         /kohya_ss/kohya_ss/sd-scripts/flux_train.py            
                         --config_file                                          
                         /kaggle/working/kohya_ss/training_data/model/config_dre
                         ambooth-20250708-231050.toml                           
ipex flag is deprecated, will be removed in Accelerate v1.10. From 2.7.0, PyTorch has all needed optimizations for Intel CPU and XPU.
/kohya_ss/kohya_ss/sd-scripts/library/deepspeed_utils.py:131: SyntaxWarning: "is not" with 'str' literal. Did you mean "!="?
  wrap_model_forward_with_torch_autocast = args.mixed_precision is not "no"
/kohya_ss/kohya_ss/sd-scripts/library/strategy_base.py:90: SyntaxWarning: invalid escape sequence '\('
  """
/kohya_ss/kohya_ss/sd-scripts/library/custom_train_functions.py:168: SyntaxWarning: invalid escape sequence '\('
  """
/kohya_ss/kohya_ss/sd-scripts/library/lpw_stable_diffusion.py:64: SyntaxWarning: invalid escape sequence '\('
  """
/kohya_ss/kohya_ss/sd-scripts/library/sdxl_lpw_stable_diffusion.py:76: SyntaxWarning: invalid escape sequence '\('
  """
2025-07-08 23:11:02 INFO     Loading settings from            ]8;id=662068;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=353969;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4651\4651]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/model/config_dreambooth-2                   
                             0250708-231050.toml...                             
2025-07-08 23:11:02 INFO     Using DreamBooth method.          ]8;id=290266;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=652861;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#115\115]8;;\
                    WARNING  ignore directory without repeats ]8;id=207180;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=345634;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#613\613]8;;\
                             /                                                  
                             繰り返し回数のないディレクトリを                   
                             無視します: .ipynb_checkpoints                     
                    INFO     prepare images.                  ]8;id=317871;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=438385;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2072\2072]8;;\
                    INFO     get image size from name of      ]8;id=40458;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=934573;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1965\1965]8;;\
                             cache files                                        
100%|███████████████████████████████████████| 10/10 [00:00<00:00, 226719.14it/s]
                    INFO     set image size from cache files: ]8;id=619594;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=333665;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1995\1995]8;;\
                             0/10                                               
                    INFO     found directory                  ]8;id=32241;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=20207;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2019\2019]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/img/1_ohwx woman contains                   
                             10 image files                                     
read caption: 100%|██████████████████████████| 10/10 [00:00<00:00, 74764.78it/s]
                    WARNING  No caption file found for 10     ]8;id=253623;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=401950;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2050\2050]8;;\
                             images. Training will continue                     
                             without captions for these                         
                             images. If class token exists,                     
                             it will be used. /                                 
                             10枚の画像にキャプションファイル                   
                             が見つかりませんでした。これらの                   
                             画像についてはキャプションなしで                   
                             学習を続行します。class                            
                             tokenが存在する場合はそれを使い                    
                             ます。                                             
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=46925;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=795466;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543397075_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=513797;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=575270;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543589299_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=535972;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=188000;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543625143_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=456357;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=78153;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681551853828_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=716374;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=85278;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681585397843_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=63319;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=574405;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2055\2055]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681585415928_36808                   
                             84077.jpg... and 5 more                            
                    INFO     10 train images with repeats.    ]8;id=938513;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=402039;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2116\2116]8;;\
                    INFO     0 reg images with repeats.       ]8;id=39608;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=898621;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2120\2120]8;;\
                    WARNING  no regularization images /       ]8;id=293386;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=318072;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2125\2125]8;;\
                             正則化画像が見つかりませんでした                   
                    INFO     [Dataset 0]                      ]8;id=211372;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=13351;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#580\580]8;;\
                               batch_size: 1                                    
                               resolution: (1024, 1024)                         
                               resize_interpolation: None                       
                               enable_bucket: True                              
                               min_bucket_reso: 256                             
                               max_bucket_reso: 2048                            
                               bucket_reso_steps: 64                            
                               bucket_no_upscale: True                          
                                                                                
                               [Subset 0 of Dataset 0]                          
                                 image_dir:                                     
                             "/kaggle/working/kohya_ss/traini                   
                             ng_data/img/1_ohwx woman"                          
                                 image_count: 10                                
                                 num_repeats: 1                                 
                                 shuffle_caption: False                         
                                 keep_tokens: 0                                 
                                 caption_dropout_rate: 0                        
                                 caption_dropout_every_n_epoc                   
                             hs: 0                                              
                                 caption_tag_dropout_rate:                      
                             0.0                                                
                                 caption_prefix: None                           
                                 caption_suffix: None                           
                                 color_aug: False                               
                                 flip_aug: False                                
                                 face_crop_aug_range: None                      
                                 random_crop: False                             
                                 token_warmup_min: 1,                           
                                 token_warmup_step: 0,                          
                                 alpha_mask: False                              
                                 resize_interpolation: None                     
                                 custom_attributes: {}                          
                                 is_reg: False                                  
                                 class_tokens: ohwx woman                       
                                 caption_extension: .txt                        
                                                                                
                                                                                
                    INFO     [Prepare dataset 0]              ]8;id=734954;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=779008;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#592\592]8;;\
                    INFO     loading image sizes.              ]8;id=998502;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=535179;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#987\987]8;;\
100%|████████████████████████████████████████| 10/10 [00:00<00:00, 43645.20it/s]
                    INFO     make buckets                     ]8;id=746320;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=188706;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1010\1010]8;;\
                    WARNING  min_bucket_reso and              ]8;id=204286;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=23414;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1027\1027]8;;\
                             max_bucket_reso are ignored if                     
                             bucket_no_upscale is set,                          
                             because bucket reso is defined                     
                             by image size automatically /                      
                             bucket_no_upscaleが指定された場                    
                             合は、bucketの解像度は画像サイズ                   
                             から自動計算されるため、min_buck                   
                             et_resoとmax_bucket_resoは無視さ                   
                             れます                                             
                    INFO     number of images (including      ]8;id=97656;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=390667;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1056\1056]8;;\
                             repeats) /                                         
                             各bucketの画像枚数（繰り返し回数                   
                             を含む）                                           
                    INFO     bucket 0: resolution (832,       ]8;id=918163;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=672676;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1061\1061]8;;\
                             1088), count: 10                                   
                    INFO     mean ar error (without repeats): ]8;id=988525;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=421621;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1069\1069]8;;\
                             0.014666190413822422                               
                    INFO     Checking the state dict: Diffusers ]8;id=717209;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=346236;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     prepare accelerator               ]8;id=331556;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=640561;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#186\186]8;;\
accelerator device: cuda
                    INFO     Building AutoEncoder              ]8;id=464197;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=907343;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#144\144]8;;\
                    INFO     Loading state dict from           ]8;id=575352;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=960489;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#149\149]8;;\
                             /kaggle/working/kohya_ss/ae.safet                  
                             ensors                                             
                    INFO     Loaded AE: <All keys matched      ]8;id=744754;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=864912;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#152\152]8;;\
                             successfully>                                      
                    INFO     [Dataset 0]                      ]8;id=517553;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=868287;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2613\2613]8;;\
                    INFO     caching latents with caching     ]8;id=737822;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=912755;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1115\1115]8;;\
                             strategy.                                          
                    INFO     caching latents...               ]8;id=250206;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=842368;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1164\1164]8;;\
100%|███████████████████████████████████████████| 10/10 [00:00<00:00, 10.49it/s]
tokenizer_config.json: 100%|███████████████████| 905/905 [00:00<00:00, 3.32MB/s]
vocab.json: 961kB [00:00, 28.8MB/s]
merges.txt: 525kB [00:00, 19.9MB/s]
special_tokens_map.json: 100%|█████████████████| 389/389 [00:00<00:00, 1.58MB/s]
tokenizer.json: 2.22MB [00:00, 60.5MB/s]
/usr/local/lib/python3.12/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
  warnings.warn(
tokenizer_config.json: 1.86kB [00:00, 12.3MB/s]
spiece.model: 100%|██████████████████████████| 792k/792k [00:00<00:00, 59.4MB/s]
special_tokens_map.json: 1.79kB [00:00, 5.39MB/s]
config.json: 100%|█████████████████████████████| 593/593 [00:00<00:00, 2.65MB/s]
You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
2025-07-08 23:11:06 INFO     Building CLIP-L                   ]8;id=84353;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=335601;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#179\179]8;;\
                    INFO     Loading state dict from           ]8;id=316089;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=578045;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#275\275]8;;\
                             /kaggle/working/kohya_ss/clip_l.s                  
                             afetensors                                         
                    INFO     Loaded CLIP-L: <All keys matched  ]8;id=854030;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=967048;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#278\278]8;;\
                             successfully>                                      
                    INFO     Loading state dict from           ]8;id=616161;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=301630;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#330\330]8;;\
                             /kaggle/working/kohya_ss/t5xxl_fp                  
                             16.safetensors                                     
2025-07-08 23:11:11 INFO     Loaded T5xxl: <All keys matched   ]8;id=332447;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=603613;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#333\333]8;;\
                             successfully>                                      
2025-07-08 23:11:13 INFO     [Dataset 0]                      ]8;id=195800;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=34574;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2635\2635]8;;\
                    INFO     caching Text Encoder outputs     ]8;id=94187;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=711693;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1298\1298]8;;\
                             with caching strategy.                             
                    INFO     checking cache validity...       ]8;id=40518;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=883383;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1309\1309]8;;\
100%|████████████████████████████████████████| 10/10 [00:00<00:00, 70611.18it/s]
                    INFO     caching Text Encoder outputs...  ]8;id=566860;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=716700;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1340\1340]8;;\
100%|███████████████████████████████████████████| 10/10 [00:00<00:00, 18.82it/s]
2025-07-08 23:11:14 INFO     cache Text Encoder outputs for    ]8;id=547136;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=851054;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#249\249]8;;\
                             sample prompt:                                     
                             /kaggle/working/kohya_ss/training                  
                             _data/model/sample/prompt.txt                      
                    INFO     Checking the state dict: Diffusers ]8;id=712480;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=618451;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     Building Flux model dev from BFL  ]8;id=472449;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=516586;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#101\101]8;;\
                             checkpoint                                         
                    INFO     Loading state dict from           ]8;id=374727;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=86374;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#118\118]8;;\
                             /kaggle/working/kohya_ss/flux1-de                  
                             v.safetensors                                      
                    INFO     Loaded Flux: <All keys matched    ]8;id=660757;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=351556;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#137\137]8;;\
                             successfully>                                      
FLUX: Gradient checkpointing enabled. CPU offload: False
number of trainable parameters: 11901408320
prepare optimizer, data loader etc.
                    INFO     use Adafactor optimizer |        ]8;id=284203;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=122824;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4963\4963]8;;\
                             {'scale_parameter': False,                         
                             'relative_step': False,                            
                             'warmup_init': False,                              
                             'weight_decay': 0.01}                              
                    WARNING  because max_grad_norm is set,    ]8;id=348689;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=446830;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4991\4991]8;;\
                             clip_grad_norm is enabled.                         
                             consider set to 0 /                                
                             max_grad_normが設定されているた                    
                             めclip_grad_normが有効になります                   
                             。0に設定して無効にしたほうがい                    
                             いかもしれません                                   
                    WARNING  constant_with_warmup will be     ]8;id=896870;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=731560;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4995\4995]8;;\
                             good /                                             
                             スケジューラはconstant_with_warm                   
                             upが良いかもしれません                             
enable full bf16 training.
running training / 学習開始
  num examples / サンプル数: 10
  num batches per epoch / 1epochのバッチ数: 10
  num epochs / epoch数: 200
  batch size per device / バッチサイズ: 1
  gradient accumulation steps / 勾配を合計するステップ数 = 1
  total optimization steps / 学習ステップ数: 2000
steps:   0%|                                           | 0/2000 [00:00<?, ?it/s]
epoch 1/200
2025-07-08 23:11:18 INFO     epoch is incremented.             ]8;id=954220;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=982012;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 0, epoch: 1                         
steps:   0%|                  | 10/2000 [00:15<49:53,  1.50s/it, avr_loss=0.481]
epoch 2/200
2025-07-08 23:11:33 INFO     epoch is incremented.             ]8;id=254276;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=55529;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 1, epoch: 2                         
steps:   1%|▏                 | 20/2000 [00:29<49:21,  1.50s/it, avr_loss=0.442]
epoch 3/200
2025-07-08 23:11:48 INFO     epoch is incremented.             ]8;id=861714;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=965360;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 2, epoch: 3                         
steps:   2%|▎                 | 30/2000 [00:44<49:00,  1.49s/it, avr_loss=0.358]
epoch 4/200
2025-07-08 23:12:03 INFO     epoch is incremented.             ]8;id=721298;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=994048;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 3, epoch: 4                         
steps:   2%|▎                 | 33/2000 [00:49<49:00,  1.49s/it, avr_loss=0.355]23:12:08-553828 INFO     The running process has been terminated.               
23:12:09-009603 INFO     Training has ended.                                    
23:13:17-105537 INFO     Start training Dreambooth...                           
23:13:17-108132 INFO     Validating lr scheduler arguments...                   
23:13:17-110192 INFO     Validating optimizer arguments...                      
23:13:17-112200 INFO     Validating /kaggle/working/kohya_ss/training_data/log  
                         existence and writability... SUCCESS                   
23:13:17-114483 INFO     Validating /kaggle/working/kohya_ss/training_data/model
                         existence and writability... SUCCESS                   
23:13:17-116759 INFO     Validating                                             
                         /kaggle/working/kohya_ss/flux1-dev.safetensors         
                         existence... SUCCESS                                   
23:13:17-119075 INFO     Validating /kaggle/working/kohya_ss/training_data/img  
                         existence... SUCCESS                                   
23:13:17-121463 INFO     Error: '.ipynb_checkpoints' does not contain an        
                         underscore, skipping...                                
23:13:17-123810 INFO     Folder 1_ohwx woman: 1 repeats found                   
23:13:17-125924 INFO     Folder 1_ohwx woman: 10 images found                   
23:13:17-127896 INFO     Folder 1_ohwx woman: 10 * 1 = 10 steps                 
23:13:17-130046 INFO     Regularization factor: 1                               
23:13:17-131985 INFO     Total steps: 10                                        
23:13:17-133797 INFO     Train batch size: 1                                    
23:13:17-135635 INFO     Gradient accumulation steps: 1                         
23:13:17-137588 INFO     Epoch: 200                                             
23:13:17-139380 INFO     max_train_steps (10 / 1 / 1 * 200 * 1) = 2000          
23:13:17-141806 INFO     lr_warmup_steps = 0                                    
23:13:17-145126 INFO     Saving training config to                              
                         /kaggle/working/kohya_ss/training_data/model/anupama_20
                         250708-231317.json...                                  
23:13:17-148886 INFO     Executing command: /usr/local/bin/accelerate launch    
                         --dynamo_backend no --dynamo_mode default              
                         --mixed_precision bf16 --num_processes 1 --num_machines
                         1 --num_cpu_threads_per_process 2                      
                         /kohya_ss/kohya_ss/sd-scripts/flux_train.py            
                         --config_file                                          
                         /kaggle/working/kohya_ss/training_data/model/config_dre
                         ambooth-20250708-231317.toml                           
ipex flag is deprecated, will be removed in Accelerate v1.10. From 2.7.0, PyTorch has all needed optimizations for Intel CPU and XPU.
2025-07-08 23:13:28 INFO     Loading settings from            ]8;id=849682;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=794751;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4651\4651]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/model/config_dreambooth-2                   
                             0250708-231317.toml...                             
2025-07-08 23:13:28 INFO     Using DreamBooth method.          ]8;id=168487;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=407458;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#115\115]8;;\
                    WARNING  ignore directory without repeats ]8;id=427694;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=725932;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#613\613]8;;\
                             /                                                  
                             繰り返し回数のないディレクトリを                   
                             無視します: .ipynb_checkpoints                     
                    INFO     prepare images.                  ]8;id=487312;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=727924;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2072\2072]8;;\
                    INFO     get image size from name of      ]8;id=332943;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=830493;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1965\1965]8;;\
                             cache files                                        
100%|███████████████████████████████████████| 10/10 [00:00<00:00, 140748.46it/s]
                    INFO     set image size from cache files: ]8;id=830349;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=853781;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1995\1995]8;;\
                             10/10                                              
                    INFO     found directory                  ]8;id=892703;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=562867;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2019\2019]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/img/1_ohwx woman contains                   
                             10 image files                                     
read caption: 100%|█████████████████████████| 10/10 [00:00<00:00, 101311.69it/s]
                    WARNING  No caption file found for 10     ]8;id=353922;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=407121;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2050\2050]8;;\
                             images. Training will continue                     
                             without captions for these                         
                             images. If class token exists,                     
                             it will be used. /                                 
                             10枚の画像にキャプションファイル                   
                             が見つかりませんでした。これらの                   
                             画像についてはキャプションなしで                   
                             学習を続行します。class                            
                             tokenが存在する場合はそれを使い                    
                             ます。                                             
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=143227;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=17723;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543397075_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=509981;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=346874;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543589299_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=73980;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=523914;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543625143_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=476175;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=447046;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681551853828_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=350325;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=498140;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681585397843_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=970670;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=936876;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2055\2055]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681585415928_36808                   
                             84077.jpg... and 5 more                            
                    INFO     10 train images with repeats.    ]8;id=265910;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=731238;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2116\2116]8;;\
                    INFO     0 reg images with repeats.       ]8;id=909402;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=403102;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2120\2120]8;;\
                    WARNING  no regularization images /       ]8;id=98739;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=882513;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2125\2125]8;;\
                             正則化画像が見つかりませんでした                   
                    INFO     [Dataset 0]                      ]8;id=830465;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=213669;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#580\580]8;;\
                               batch_size: 1                                    
                               resolution: (1024, 1024)                         
                               resize_interpolation: None                       
                               enable_bucket: True                              
                               min_bucket_reso: 256                             
                               max_bucket_reso: 2048                            
                               bucket_reso_steps: 64                            
                               bucket_no_upscale: True                          
                                                                                
                               [Subset 0 of Dataset 0]                          
                                 image_dir:                                     
                             "/kaggle/working/kohya_ss/traini                   
                             ng_data/img/1_ohwx woman"                          
                                 image_count: 10                                
                                 num_repeats: 1                                 
                                 shuffle_caption: False                         
                                 keep_tokens: 0                                 
                                 caption_dropout_rate: 0                        
                                 caption_dropout_every_n_epoc                   
                             hs: 0                                              
                                 caption_tag_dropout_rate:                      
                             0.0                                                
                                 caption_prefix: None                           
                                 caption_suffix: None                           
                                 color_aug: False                               
                                 flip_aug: False                                
                                 face_crop_aug_range: None                      
                                 random_crop: False                             
                                 token_warmup_min: 1,                           
                                 token_warmup_step: 0,                          
                                 alpha_mask: False                              
                                 resize_interpolation: None                     
                                 custom_attributes: {}                          
                                 is_reg: False                                  
                                 class_tokens: ohwx woman                       
                                 caption_extension: .txt                        
                                                                                
                                                                                
                    INFO     [Prepare dataset 0]              ]8;id=89760;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=418732;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#592\592]8;;\
                    INFO     loading image sizes.              ]8;id=861027;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=164440;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#987\987]8;;\
100%|███████████████████████████████████████| 10/10 [00:00<00:00, 460912.53it/s]
                    INFO     make buckets                     ]8;id=173662;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=442272;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1010\1010]8;;\
                    WARNING  min_bucket_reso and              ]8;id=303511;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=445436;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1027\1027]8;;\
                             max_bucket_reso are ignored if                     
                             bucket_no_upscale is set,                          
                             because bucket reso is defined                     
                             by image size automatically /                      
                             bucket_no_upscaleが指定された場                    
                             合は、bucketの解像度は画像サイズ                   
                             から自動計算されるため、min_buck                   
                             et_resoとmax_bucket_resoは無視さ                   
                             れます                                             
                    INFO     number of images (including      ]8;id=672803;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=766696;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1056\1056]8;;\
                             repeats) /                                         
                             各bucketの画像枚数（繰り返し回数                   
                             を含む）                                           
                    INFO     bucket 0: resolution (832,       ]8;id=320572;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=911799;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1061\1061]8;;\
                             1088), count: 10                                   
                    INFO     mean ar error (without repeats): ]8;id=660684;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=285017;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1069\1069]8;;\
                             0.014666190413822422                               
                    INFO     Checking the state dict: Diffusers ]8;id=717209;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=346236;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     prepare accelerator               ]8;id=331556;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=640561;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#186\186]8;;\
accelerator device: cuda
                    INFO     Building AutoEncoder              ]8;id=464197;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=907343;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#144\144]8;;\
                    INFO     Loading state dict from           ]8;id=575352;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=960489;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#149\149]8;;\
                             /kaggle/working/kohya_ss/ae.safet                  
                             ensors                                             
                    INFO     Loaded AE: <All keys matched      ]8;id=744754;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=864912;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#152\152]8;;\
                             successfully>                                      
                    INFO     [Dataset 0]                      ]8;id=517553;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=868287;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2613\2613]8;;\
                    INFO     caching latents with caching     ]8;id=737822;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=912755;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1115\1115]8;;\
                             strategy.                                          
                    INFO     caching latents...               ]8;id=250206;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=842368;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1164\1164]8;;\
100%|█████████████████████████████████████████| 10/10 [00:00<00:00, 7891.45it/s]
/usr/local/lib/python3.12/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
  warnings.warn(
You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
2025-07-08 23:13:29 INFO     Building CLIP-L                   ]8;id=84353;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=335601;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#179\179]8;;\
                    INFO     Loading state dict from           ]8;id=316089;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=578045;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#275\275]8;;\
                             /kaggle/working/kohya_ss/clip_l.s                  
                             afetensors                                         
2025-07-08 23:13:30 INFO     Loaded CLIP-L: <All keys matched  ]8;id=854030;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=967048;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#278\278]8;;\
                             successfully>                                      
                    INFO     Loading state dict from           ]8;id=616161;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=301630;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#330\330]8;;\
                             /kaggle/working/kohya_ss/t5xxl_fp                  
                             16.safetensors                                     
2025-07-08 23:13:35 INFO     Loaded T5xxl: <All keys matched   ]8;id=332447;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=603613;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#333\333]8;;\
                             successfully>                                      
2025-07-08 23:13:37 INFO     [Dataset 0]                      ]8;id=195800;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=34574;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2635\2635]8;;\
                    INFO     caching Text Encoder outputs     ]8;id=94187;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=711693;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1298\1298]8;;\
                             with caching strategy.                             
                    INFO     checking cache validity...       ]8;id=40518;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=883383;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1309\1309]8;;\
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                    INFO     no Text Encoder outputs to cache ]8;id=566860;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=716700;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1336\1336]8;;\
                    INFO     cache Text Encoder outputs for    ]8;id=547136;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=851054;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#249\249]8;;\
                             sample prompt:                                     
                             /kaggle/working/kohya_ss/training                  
                             _data/model/sample/prompt.txt                      
                    INFO     cache Text Encoder outputs for    ]8;id=618451;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=865351;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#259\259]8;;\
                             prompt: ohwx woman in a                            
                             sophisticated winter ensemble:                     
                             wool coat in burgundy, matching                    
                             beret, cashmere turtleneck, plaid                  
                             wool skirt below knees, leather                    
                             gloves, classic ice skates,                        
                             Italian wool scarf, city plaza                     
                             setting with snow, twilight                        
                             atmosphere with twinkling lights                   
                    INFO     cache Text Encoder outputs for    ]8;id=472449;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=516586;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#259\259]8;;\
                             prompt:                                            
                    INFO     Checking the state dict: Diffusers ]8;id=831861;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=374727;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     Building Flux model dev from BFL  ]8;id=615592;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=660757;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#101\101]8;;\
                             checkpoint                                         
                    INFO     Loading state dict from           ]8;id=767022;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=284203;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#118\118]8;;\
                             /kaggle/working/kohya_ss/flux1-de                  
                             v.safetensors                                      
                    INFO     Loaded Flux: <All keys matched    ]8;id=178763;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=348689;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#137\137]8;;\
                             successfully>                                      
FLUX: Gradient checkpointing enabled. CPU offload: False
number of trainable parameters: 11901408320
prepare optimizer, data loader etc.
                    INFO     use Adafactor optimizer |        ]8;id=153467;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=896870;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4963\4963]8;;\
                             {'scale_parameter': False,                         
                             'relative_step': False,                            
                             'warmup_init': False,                              
                             'weight_decay': 0.01}                              
                    WARNING  because max_grad_norm is set,    ]8;id=665013;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=954220;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4991\4991]8;;\
                             clip_grad_norm is enabled.                         
                             consider set to 0 /                                
                             max_grad_normが設定されているた                    
                             めclip_grad_normが有効になります                   
                             。0に設定して無効にしたほうがい                    
                             いかもしれません                                   
                    WARNING  constant_with_warmup will be     ]8;id=27993;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=130488;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4995\4995]8;;\
                             good /                                             
                             スケジューラはconstant_with_warm                   
                             upが良いかもしれません                             
enable full bf16 training.
running training / 学習開始
  num examples / サンプル数: 10
  num batches per epoch / 1epochのバッチ数: 10
  num epochs / epoch数: 200
  batch size per device / バッチサイズ: 1
  gradient accumulation steps / 勾配を合計するステップ数 = 1
  total optimization steps / 学習ステップ数: 2000
steps:   0%|                                           | 0/2000 [00:00<?, ?it/s]
epoch 1/200
2025-07-08 23:13:42 INFO     epoch is incremented.             ]8;id=125509;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=410212;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 0, epoch: 1                         
steps:   0%|                  | 10/2000 [00:14<49:40,  1.50s/it, avr_loss=0.436]
epoch 2/200
2025-07-08 23:13:57 INFO     epoch is incremented.             ]8;id=575133;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=153951;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 1, epoch: 2                         
steps:   1%|▏                 | 20/2000 [00:29<49:09,  1.49s/it, avr_loss=0.436]
epoch 3/200
2025-07-08 23:14:12 INFO     epoch is incremented.             ]8;id=843482;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=823829;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 2, epoch: 3                         
steps:   2%|▎                 | 30/2000 [00:44<48:48,  1.49s/it, avr_loss=0.398]
epoch 4/200
2025-07-08 23:14:27 INFO     epoch is incremented.             ]8;id=490053;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=119323;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 3, epoch: 4                         
steps:   2%|▍                  | 40/2000 [00:59<48:31,  1.49s/it, avr_loss=0.34]
epoch 5/200
2025-07-08 23:14:42 INFO     epoch is incremented.             ]8;id=657989;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=97015;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 4, epoch: 5                         
steps:   2%|▍                 | 50/2000 [01:14<48:18,  1.49s/it, avr_loss=0.367]2025-07-08 23:14:56 INFO                                  ]8;id=143603;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=373594;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=765615;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=773136;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 50                                       
                    INFO     prompt: ohwx woman in a     ]8;id=72205;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=600184;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=763972;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=505835;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=61896;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=909214;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=215529;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=450855;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=853463;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=9080;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:   2%|▍                 | 50/2000 [01:16<49:53,  1.54s/it, avr_loss=0.386]
epoch 6/200
2025-07-08 23:14:59 INFO     epoch is incremented.             ]8;id=916492;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=979861;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 5, epoch: 6                         
steps:   3%|▌                 | 60/2000 [01:31<49:20,  1.53s/it, avr_loss=0.426]
epoch 7/200
2025-07-08 23:15:14 INFO     epoch is incremented.             ]8;id=78405;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=663321;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 6, epoch: 7                         
steps:   4%|▋                 | 70/2000 [01:46<48:50,  1.52s/it, avr_loss=0.337]
epoch 8/200
2025-07-08 23:15:28 INFO     epoch is incremented.             ]8;id=762885;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=654375;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 7, epoch: 8                         
steps:   4%|▋                 | 80/2000 [02:01<48:26,  1.51s/it, avr_loss=0.416]
epoch 9/200
2025-07-08 23:15:43 INFO     epoch is incremented.             ]8;id=340367;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=192900;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 8, epoch: 9                         
steps:   4%|▊                 | 90/2000 [02:15<48:05,  1.51s/it, avr_loss=0.393]
epoch 10/200
2025-07-08 23:15:58 INFO     epoch is incremented.             ]8;id=143788;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=41086;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 9, epoch: 10                        
steps:   5%|▊                | 100/2000 [02:30<47:42,  1.51s/it, avr_loss=0.382]2025-07-08 23:16:13 INFO                                  ]8;id=84498;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=860017;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=23662;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=978417;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 100                                      
                    INFO     prompt: ohwx woman in a     ]8;id=199749;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=377066;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=818600;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=458792;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=915120;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=887548;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=211764;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=708851;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=134376;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=510371;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 11/200
2025-07-08 23:16:15 INFO     epoch is incremented.             ]8;id=550898;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=584054;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 10, epoch: 11                       
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epoch 12/200
2025-07-08 23:16:30 INFO     epoch is incremented.             ]8;id=888778;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=807651;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 11, epoch: 12                       
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epoch 13/200
2025-07-08 23:16:45 INFO     epoch is incremented.             ]8;id=570815;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=412976;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 12, epoch: 13                       
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epoch 14/200
2025-07-08 23:16:59 INFO     epoch is incremented.             ]8;id=868697;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=402073;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 13, epoch: 14                       
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epoch 15/200
2025-07-08 23:17:14 INFO     epoch is incremented.             ]8;id=864922;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=564408;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 14, epoch: 15                       
steps:   8%|█▎               | 150/2000 [03:46<46:36,  1.51s/it, avr_loss=0.388]2025-07-08 23:17:29 INFO                                  ]8;id=945566;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=926394;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=181667;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=891404;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 150                                      
                    INFO     prompt: ohwx woman in a     ]8;id=352434;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=156715;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=83904;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=654840;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=512435;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=958502;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=680856;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=404695;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=842250;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=535670;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 16/200
2025-07-08 23:17:31 INFO     epoch is incremented.             ]8;id=740395;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=513656;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
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epoch 17/200
2025-07-08 23:17:46 INFO     epoch is incremented.             ]8;id=409083;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=529469;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 16, epoch: 17                       
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epoch 18/200
2025-07-08 23:18:01 INFO     epoch is incremented.             ]8;id=646941;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=612646;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 17, epoch: 18                       
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epoch 19/200
2025-07-08 23:18:16 INFO     epoch is incremented.             ]8;id=333878;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=495663;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 18, epoch: 19                       
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epoch 20/200
2025-07-08 23:18:30 INFO     epoch is incremented.             ]8;id=466788;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=55608;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 19, epoch: 20                       
steps:  10%|█▋               | 200/2000 [05:02<45:26,  1.51s/it, avr_loss=0.381]2025-07-08 23:18:45 INFO                                  ]8;id=500889;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=304710;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=676294;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=558154;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 200                                      
                    INFO     prompt: ohwx woman in a     ]8;id=257233;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=500194;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=159514;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=921087;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=622179;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=343792;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=506124;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=958328;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=64290;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=279341;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  10%|█▋               | 200/2000 [05:05<45:47,  1.53s/it, avr_loss=0.401]
epoch 21/200
2025-07-08 23:18:47 INFO     epoch is incremented.             ]8;id=889256;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=715403;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 20, epoch: 21                       
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epoch 22/200
2025-07-08 23:19:02 INFO     epoch is incremented.             ]8;id=841901;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=173792;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 21, epoch: 22                       
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epoch 23/200
2025-07-08 23:19:17 INFO     epoch is incremented.             ]8;id=904864;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=681377;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 22, epoch: 23                       
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epoch 24/200
2025-07-08 23:19:32 INFO     epoch is incremented.             ]8;id=336218;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=567170;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 23, epoch: 24                       
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epoch 25/200
2025-07-08 23:19:47 INFO     epoch is incremented.             ]8;id=713708;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=766263;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 24, epoch: 25                       
steps:  12%|██▏              | 250/2000 [06:19<44:13,  1.52s/it, avr_loss=0.351]2025-07-08 23:20:01 INFO                                  ]8;id=531457;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=232298;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=482574;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=4914;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 250                                      
                    INFO     prompt: ohwx woman in a     ]8;id=346350;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=420991;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=269749;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=816331;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=255309;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=109245;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=726190;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=669294;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=220430;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=973868;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 26/200
2025-07-08 23:20:04 INFO     epoch is incremented.             ]8;id=536975;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=128732;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 25, epoch: 26                       
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epoch 27/200
2025-07-08 23:20:18 INFO     epoch is incremented.             ]8;id=447483;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=945406;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 26, epoch: 27                       
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epoch 28/200
2025-07-08 23:20:33 INFO     epoch is incremented.             ]8;id=487713;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=227056;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 27, epoch: 28                       
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epoch 29/200
2025-07-08 23:20:48 INFO     epoch is incremented.             ]8;id=777356;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=307764;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 28, epoch: 29                       
steps:  14%|██▍              | 290/2000 [07:20<43:16,  1.52s/it, avr_loss=0.366]
epoch 30/200
2025-07-08 23:21:03 INFO     epoch is incremented.             ]8;id=374688;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=793766;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 29, epoch: 30                       
steps:  15%|██▌              | 300/2000 [07:35<42:58,  1.52s/it, avr_loss=0.353]2025-07-08 23:21:17 INFO                                  ]8;id=759633;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=603046;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=909104;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=41546;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 300                                      
                    INFO     prompt: ohwx woman in a     ]8;id=388466;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=867977;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=149844;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=207916;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=132920;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=497013;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=861883;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=653497;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=192612;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=768261;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 31/200
2025-07-08 23:21:20 INFO     epoch is incremented.             ]8;id=803603;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=841069;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 30, epoch: 31                       
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epoch 32/200
2025-07-08 23:21:34 INFO     epoch is incremented.             ]8;id=959912;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=272011;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 31, epoch: 32                       
steps:  16%|██▋              | 320/2000 [08:06<42:36,  1.52s/it, avr_loss=0.284]
epoch 33/200
2025-07-08 23:21:49 INFO     epoch is incremented.             ]8;id=859920;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=447377;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 32, epoch: 33                       
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epoch 34/200
2025-07-08 23:22:04 INFO     epoch is incremented.             ]8;id=296304;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=129231;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 33, epoch: 34                       
steps:  17%|██▉              | 340/2000 [08:36<42:01,  1.52s/it, avr_loss=0.335]
epoch 35/200
2025-07-08 23:22:19 INFO     epoch is incremented.             ]8;id=846206;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=937516;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 34, epoch: 35                       
steps:  18%|██▉              | 350/2000 [08:51<41:43,  1.52s/it, avr_loss=0.408]2025-07-08 23:22:33 INFO                                  ]8;id=134606;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=774142;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=346268;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=924704;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 350                                      
                    INFO     prompt: ohwx woman in a     ]8;id=173510;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=660857;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=895352;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=298087;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=352511;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=982424;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=236362;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=982353;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=208973;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=956588;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  18%|██▉              | 350/2000 [08:53<41:54,  1.52s/it, avr_loss=0.407]
epoch 36/200
2025-07-08 23:22:36 INFO     epoch is incremented.             ]8;id=337665;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=519166;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 35, epoch: 36                       
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epoch 37/200
2025-07-08 23:22:50 INFO     epoch is incremented.             ]8;id=179836;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=44547;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 36, epoch: 37                       
steps:  18%|███▏             | 370/2000 [09:22<41:19,  1.52s/it, avr_loss=0.351]
epoch 38/200
2025-07-08 23:23:05 INFO     epoch is incremented.             ]8;id=665396;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=586149;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 37, epoch: 38                       
steps:  19%|███▏             | 380/2000 [09:37<41:02,  1.52s/it, avr_loss=0.429]
epoch 39/200
2025-07-08 23:23:20 INFO     epoch is incremented.             ]8;id=280969;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=425174;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 38, epoch: 39                       
steps:  20%|███▌              | 390/2000 [09:52<40:45,  1.52s/it, avr_loss=0.33]
epoch 40/200
2025-07-08 23:23:35 INFO     epoch is incremented.             ]8;id=605733;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=122362;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 39, epoch: 40                       
steps:  20%|███▍             | 400/2000 [10:07<40:28,  1.52s/it, avr_loss=0.293]2025-07-08 23:23:49 INFO                                  ]8;id=811866;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=995478;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=856735;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=601523;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 400                                      
                    INFO     prompt: ohwx woman in a     ]8;id=51858;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=670588;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=453257;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=334305;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=425613;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=997637;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=564227;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=671520;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=305383;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=25878;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 41/200
2025-07-08 23:23:52 INFO     epoch is incremented.             ]8;id=71225;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=373742;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 40, epoch: 41                       
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epoch 42/200
2025-07-08 23:24:06 INFO     epoch is incremented.             ]8;id=280154;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=346368;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 41, epoch: 42                       
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epoch 43/200
2025-07-08 23:24:21 INFO     epoch is incremented.             ]8;id=853473;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=296021;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 42, epoch: 43                       
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epoch 44/200
2025-07-08 23:24:36 INFO     epoch is incremented.             ]8;id=16790;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=45391;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 43, epoch: 44                       
steps:  22%|███▋             | 440/2000 [11:08<39:30,  1.52s/it, avr_loss=0.346]
epoch 45/200
2025-07-08 23:24:51 INFO     epoch is incremented.             ]8;id=470479;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=190532;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 44, epoch: 45                       
steps:  22%|███▊             | 442/2000 [11:11<39:27,  1.52s/it, avr_loss=0.331]23:24:55-334818 INFO     The running process has been terminated.               
23:24:55-679537 INFO     Training has ended.                                    
23:25:17-435498 INFO     Start training Dreambooth...                           
23:25:17-438059 INFO     Validating lr scheduler arguments...                   
23:25:17-440217 INFO     Validating optimizer arguments...                      
23:25:17-442366 INFO     Validating /kaggle/working/kohya_ss/training_data/log  
                         existence and writability... SUCCESS                   
23:25:17-444686 INFO     Validating /kaggle/working/kohya_ss/training_data/model
                         existence and writability... SUCCESS                   
23:25:17-447030 INFO     Validating                                             
                         /kaggle/working/kohya_ss/flux1-dev.safetensors         
                         existence... SUCCESS                                   
23:25:17-449270 INFO     Validating /kaggle/working/kohya_ss/training_data/img  
                         existence... SUCCESS                                   
23:25:17-451631 INFO     Error: '.ipynb_checkpoints' does not contain an        
                         underscore, skipping...                                
23:25:17-454015 INFO     Folder 1_ohwx woman: 1 repeats found                   
23:25:17-456135 INFO     Folder 1_ohwx woman: 10 images found                   
23:25:17-458096 INFO     Folder 1_ohwx woman: 10 * 1 = 10 steps                 
23:25:17-460226 INFO     Regularization factor: 1                               
23:25:17-462095 INFO     Total steps: 10                                        
23:25:17-463926 INFO     Train batch size: 1                                    
23:25:17-465906 INFO     Gradient accumulation steps: 1                         
23:25:17-467824 INFO     Epoch: 200                                             
23:25:17-469572 INFO     max_train_steps (10 / 1 / 1 * 200 * 1) = 2000          
23:25:17-471876 INFO     lr_warmup_steps = 0                                    
23:25:17-475614 INFO     Saving training config to                              
                         /kaggle/working/kohya_ss/training_data/model/anupama_20
                         250708-232517.json...                                  
23:25:17-479330 INFO     Executing command: /usr/local/bin/accelerate launch    
                         --dynamo_backend no --dynamo_mode default              
                         --mixed_precision bf16 --num_processes 1 --num_machines
                         1 --num_cpu_threads_per_process 2                      
                         /kohya_ss/kohya_ss/sd-scripts/flux_train.py            
                         --config_file                                          
                         /kaggle/working/kohya_ss/training_data/model/config_dre
                         ambooth-20250708-232517.toml                           
ipex flag is deprecated, will be removed in Accelerate v1.10. From 2.7.0, PyTorch has all needed optimizations for Intel CPU and XPU.
2025-07-08 23:25:28 INFO     Loading settings from            ]8;id=532249;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=210848;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4651\4651]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/model/config_dreambooth-2                   
                             0250708-232517.toml...                             
2025-07-08 23:25:28 INFO     Using DreamBooth method.          ]8;id=13633;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=286667;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#115\115]8;;\
                    WARNING  ignore directory without repeats ]8;id=607306;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=67304;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#613\613]8;;\
                             /                                                  
                             繰り返し回数のないディレクトリを                   
                             無視します: .ipynb_checkpoints                     
                    INFO     prepare images.                  ]8;id=222457;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=632622;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2072\2072]8;;\
                    INFO     get image size from name of      ]8;id=162095;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=220141;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1965\1965]8;;\
                             cache files                                        
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                    INFO     set image size from cache files: ]8;id=743830;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=778420;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1995\1995]8;;\
                             10/10                                              
                    INFO     found directory                  ]8;id=971520;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=857756;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2019\2019]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/img/1_ohwx woman contains                   
                             10 image files                                     
read caption: 100%|█████████████████████████| 10/10 [00:00<00:00, 100582.83it/s]
                    WARNING  No caption file found for 10     ]8;id=719602;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=380209;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2050\2050]8;;\
                             images. Training will continue                     
                             without captions for these                         
                             images. If class token exists,                     
                             it will be used. /                                 
                             10枚の画像にキャプションファイル                   
                             が見つかりませんでした。これらの                   
                             画像についてはキャプションなしで                   
                             学習を続行します。class                            
                             tokenが存在する場合はそれを使い                    
                             ます。                                             
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=514911;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=11898;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543397075_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=498007;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=974945;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543589299_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=718203;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=205740;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543625143_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=677786;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=812621;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681551853828_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=371115;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=211320;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681585397843_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=291648;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=734281;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2055\2055]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681585415928_36808                   
                             84077.jpg... and 5 more                            
                    INFO     10 train images with repeats.    ]8;id=814359;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=377157;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2116\2116]8;;\
                    INFO     0 reg images with repeats.       ]8;id=768878;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=619648;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2120\2120]8;;\
                    WARNING  no regularization images /       ]8;id=84504;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=750710;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2125\2125]8;;\
                             正則化画像が見つかりませんでした                   
                    INFO     [Dataset 0]                      ]8;id=899714;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=499530;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#580\580]8;;\
                               batch_size: 1                                    
                               resolution: (1024, 1024)                         
                               resize_interpolation: None                       
                               enable_bucket: True                              
                               min_bucket_reso: 256                             
                               max_bucket_reso: 2048                            
                               bucket_reso_steps: 64                            
                               bucket_no_upscale: True                          
                                                                                
                               [Subset 0 of Dataset 0]                          
                                 image_dir:                                     
                             "/kaggle/working/kohya_ss/traini                   
                             ng_data/img/1_ohwx woman"                          
                                 image_count: 10                                
                                 num_repeats: 1                                 
                                 shuffle_caption: False                         
                                 keep_tokens: 0                                 
                                 caption_dropout_rate: 0                        
                                 caption_dropout_every_n_epoc                   
                             hs: 0                                              
                                 caption_tag_dropout_rate:                      
                             0.0                                                
                                 caption_prefix: None                           
                                 caption_suffix: None                           
                                 color_aug: False                               
                                 flip_aug: False                                
                                 face_crop_aug_range: None                      
                                 random_crop: False                             
                                 token_warmup_min: 1,                           
                                 token_warmup_step: 0,                          
                                 alpha_mask: False                              
                                 resize_interpolation: None                     
                                 custom_attributes: {}                          
                                 is_reg: False                                  
                                 class_tokens: ohwx woman                       
                                 caption_extension: .txt                        
                                                                                
                                                                                
                    INFO     [Prepare dataset 0]              ]8;id=258766;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=561612;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#592\592]8;;\
                    INFO     loading image sizes.              ]8;id=203155;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=167041;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#987\987]8;;\
100%|███████████████████████████████████████| 10/10 [00:00<00:00, 471270.11it/s]
                    INFO     make buckets                     ]8;id=400519;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=646146;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1010\1010]8;;\
                    WARNING  min_bucket_reso and              ]8;id=440307;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=508680;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1027\1027]8;;\
                             max_bucket_reso are ignored if                     
                             bucket_no_upscale is set,                          
                             because bucket reso is defined                     
                             by image size automatically /                      
                             bucket_no_upscaleが指定された場                    
                             合は、bucketの解像度は画像サイズ                   
                             から自動計算されるため、min_buck                   
                             et_resoとmax_bucket_resoは無視さ                   
                             れます                                             
                    INFO     number of images (including      ]8;id=937319;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=721430;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1056\1056]8;;\
                             repeats) /                                         
                             各bucketの画像枚数（繰り返し回数                   
                             を含む）                                           
                    INFO     bucket 0: resolution (832,       ]8;id=301548;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=866737;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1061\1061]8;;\
                             1088), count: 10                                   
                    INFO     mean ar error (without repeats): ]8;id=374969;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=353955;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1069\1069]8;;\
                             0.014666190413822422                               
                    INFO     Checking the state dict: Diffusers ]8;id=717209;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=346236;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     prepare accelerator               ]8;id=331556;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=640561;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#186\186]8;;\
accelerator device: cuda
                    INFO     Building AutoEncoder              ]8;id=464197;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=907343;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#144\144]8;;\
                    INFO     Loading state dict from           ]8;id=575352;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=960489;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#149\149]8;;\
                             /kaggle/working/kohya_ss/ae.safet                  
                             ensors                                             
                    INFO     Loaded AE: <All keys matched      ]8;id=744754;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=864912;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#152\152]8;;\
                             successfully>                                      
2025-07-08 23:25:29 INFO     [Dataset 0]                      ]8;id=517553;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=868287;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2613\2613]8;;\
                    INFO     caching latents with caching     ]8;id=737822;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=912755;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1115\1115]8;;\
                             strategy.                                          
                    INFO     caching latents...               ]8;id=250206;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=842368;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1164\1164]8;;\
100%|█████████████████████████████████████████| 10/10 [00:00<00:00, 7491.17it/s]
/usr/local/lib/python3.12/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
  warnings.warn(
You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
2025-07-08 23:25:30 INFO     Building CLIP-L                   ]8;id=84353;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=335601;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#179\179]8;;\
                    INFO     Loading state dict from           ]8;id=316089;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=578045;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#275\275]8;;\
                             /kaggle/working/kohya_ss/clip_l.s                  
                             afetensors                                         
                    INFO     Loaded CLIP-L: <All keys matched  ]8;id=854030;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=967048;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#278\278]8;;\
                             successfully>                                      
                    INFO     Loading state dict from           ]8;id=616161;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=301630;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#330\330]8;;\
                             /kaggle/working/kohya_ss/t5xxl_fp                  
                             16.safetensors                                     
2025-07-08 23:25:35 INFO     Loaded T5xxl: <All keys matched   ]8;id=332447;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=603613;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#333\333]8;;\
                             successfully>                                      
2025-07-08 23:25:37 INFO     [Dataset 0]                      ]8;id=195800;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=34574;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2635\2635]8;;\
                    INFO     caching Text Encoder outputs     ]8;id=94187;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=711693;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1298\1298]8;;\
                             with caching strategy.                             
                    INFO     checking cache validity...       ]8;id=40518;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=883383;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1309\1309]8;;\
100%|█████████████████████████████████████████| 10/10 [00:00<00:00, 4471.06it/s]
                    INFO     no Text Encoder outputs to cache ]8;id=566860;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=716700;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1336\1336]8;;\
                    INFO     cache Text Encoder outputs for    ]8;id=547136;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=851054;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#249\249]8;;\
                             sample prompt:                                     
                             /kaggle/working/kohya_ss/training                  
                             _data/model/sample/prompt.txt                      
                    INFO     cache Text Encoder outputs for    ]8;id=618451;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=865351;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#259\259]8;;\
                             prompt: ohwx woman in a                            
                             sophisticated winter ensemble:                     
                             wool coat in burgundy, matching                    
                             beret, cashmere turtleneck, plaid                  
                             wool skirt below knees, leather                    
                             gloves, classic ice skates,                        
                             Italian wool scarf, city plaza                     
                             setting with snow, twilight                        
                             atmosphere with twinkling lights                   
                    INFO     cache Text Encoder outputs for    ]8;id=472449;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=516586;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#259\259]8;;\
                             prompt:                                            
                    INFO     Checking the state dict: Diffusers ]8;id=831861;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=374727;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     Building Flux model dev from BFL  ]8;id=615592;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=660757;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#101\101]8;;\
                             checkpoint                                         
2025-07-08 23:25:38 INFO     Loading state dict from           ]8;id=767022;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=284203;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#118\118]8;;\
                             /kaggle/working/kohya_ss/flux1-de                  
                             v.safetensors                                      
                    INFO     Loaded Flux: <All keys matched    ]8;id=178763;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=348689;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#137\137]8;;\
                             successfully>                                      
FLUX: Gradient checkpointing enabled. CPU offload: False
number of trainable parameters: 11901408320
prepare optimizer, data loader etc.
                    INFO     use Adafactor optimizer |        ]8;id=153467;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=896870;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4963\4963]8;;\
                             {'scale_parameter': False,                         
                             'relative_step': False,                            
                             'warmup_init': False,                              
                             'weight_decay': 0.01}                              
                    WARNING  because max_grad_norm is set,    ]8;id=665013;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=954220;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4991\4991]8;;\
                             clip_grad_norm is enabled.                         
                             consider set to 0 /                                
                             max_grad_normが設定されているた                    
                             めclip_grad_normが有効になります                   
                             。0に設定して無効にしたほうがい                    
                             いかもしれません                                   
                    WARNING  constant_with_warmup will be     ]8;id=27993;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=130488;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4995\4995]8;;\
                             good /                                             
                             スケジューラはconstant_with_warm                   
                             upが良いかもしれません                             
enable full bf16 training.
running training / 学習開始
  num examples / サンプル数: 10
  num batches per epoch / 1epochのバッチ数: 10
  num epochs / epoch数: 200
  batch size per device / バッチサイズ: 1
  gradient accumulation steps / 勾配を合計するステップ数 = 1
  total optimization steps / 学習ステップ数: 2000
steps:   0%|                                           | 0/2000 [00:00<?, ?it/s]
epoch 1/200
2025-07-08 23:25:42 INFO     epoch is incremented.             ]8;id=125509;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=410212;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 0, epoch: 1                         
steps:   0%|                  | 10/2000 [00:14<49:41,  1.50s/it, avr_loss=0.421]
epoch 2/200
2025-07-08 23:25:57 INFO     epoch is incremented.             ]8;id=353509;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=14275;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 1, epoch: 2                         
steps:   1%|▏                 | 20/2000 [00:29<49:10,  1.49s/it, avr_loss=0.384]
epoch 3/200
2025-07-08 23:26:12 INFO     epoch is incremented.             ]8;id=116384;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=143640;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 2, epoch: 3                         
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epoch 4/200
2025-07-08 23:26:27 INFO     epoch is incremented.             ]8;id=302938;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=641189;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 3, epoch: 4                         
steps:   2%|▎                 | 40/2000 [00:59<48:34,  1.49s/it, avr_loss=0.399]
epoch 5/200
2025-07-08 23:26:41 INFO     epoch is incremented.             ]8;id=306499;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=521238;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 4, epoch: 5                         
steps:   2%|▍                 | 50/2000 [01:14<48:21,  1.49s/it, avr_loss=0.358]2025-07-08 23:26:56 INFO                                  ]8;id=271005;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=461927;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=27465;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=301182;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 50                                       
                    INFO     prompt: ohwx woman in a     ]8;id=991784;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=961424;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=302873;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=32386;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=633569;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=213921;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=943782;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=705359;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=492791;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=367841;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:   2%|▍                 | 50/2000 [01:16<49:58,  1.54s/it, avr_loss=0.338]
epoch 6/200
2025-07-08 23:26:59 INFO     epoch is incremented.             ]8;id=840729;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=215092;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 5, epoch: 6                         
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epoch 7/200
2025-07-08 23:27:14 INFO     epoch is incremented.             ]8;id=55282;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=775901;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 6, epoch: 7                         
steps:   4%|▋                 | 70/2000 [01:46<48:53,  1.52s/it, avr_loss=0.354]
epoch 8/200
2025-07-08 23:27:28 INFO     epoch is incremented.             ]8;id=194297;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=327353;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 7, epoch: 8                         
steps:   4%|▊                  | 80/2000 [02:01<48:29,  1.52s/it, avr_loss=0.38]
epoch 9/200
2025-07-08 23:27:43 INFO     epoch is incremented.             ]8;id=505595;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=679486;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 8, epoch: 9                         
steps:   4%|▊                 | 90/2000 [02:16<48:07,  1.51s/it, avr_loss=0.415]
epoch 10/200
2025-07-08 23:27:58 INFO     epoch is incremented.             ]8;id=138944;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=819919;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 9, epoch: 10                        
steps:   5%|▉                  | 100/2000 [02:30<47:44,  1.51s/it, avr_loss=0.4]2025-07-08 23:28:13 INFO                                  ]8;id=767642;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=834015;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=761154;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=584729;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 100                                      
                    INFO     prompt: ohwx woman in a     ]8;id=135346;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=347965;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=30515;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=94810;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=651776;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=740078;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=597147;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=239032;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=603458;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=611652;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:   5%|▊                | 100/2000 [02:33<48:32,  1.53s/it, avr_loss=0.395]
epoch 11/200
2025-07-08 23:28:15 INFO     epoch is incremented.             ]8;id=740937;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=561484;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 10, epoch: 11                       
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epoch 12/200
2025-07-08 23:28:30 INFO     epoch is incremented.             ]8;id=829046;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=954016;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 11, epoch: 12                       
steps:   6%|█                 | 120/2000 [03:02<47:46,  1.52s/it, avr_loss=0.39]
epoch 13/200
2025-07-08 23:28:45 INFO     epoch is incremented.             ]8;id=580195;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=262595;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 12, epoch: 13                       
steps:   6%|█                | 130/2000 [03:17<47:25,  1.52s/it, avr_loss=0.406]
epoch 14/200
2025-07-08 23:29:00 INFO     epoch is incremented.             ]8;id=719583;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=325340;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 13, epoch: 14                       
steps:   7%|█▏               | 140/2000 [03:32<47:05,  1.52s/it, avr_loss=0.415]
epoch 15/200
2025-07-08 23:29:15 INFO     epoch is incremented.             ]8;id=185277;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=496071;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 14, epoch: 15                       
steps:   8%|█▎                | 150/2000 [03:47<46:44,  1.52s/it, avr_loss=0.32]2025-07-08 23:29:29 INFO                                  ]8;id=847619;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=758151;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=713890;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=280841;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 150                                      
                    INFO     prompt: ohwx woman in a     ]8;id=676424;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=827542;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=746193;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=977190;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=790285;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=29743;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=807033;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=844978;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=814099;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=20087;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:   8%|█▎               | 150/2000 [03:49<47:12,  1.53s/it, avr_loss=0.316]
epoch 16/200
2025-07-08 23:29:32 INFO     epoch is incremented.             ]8;id=347331;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=709056;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 15, epoch: 16                       
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epoch 17/200
2025-07-08 23:29:46 INFO     epoch is incremented.             ]8;id=628474;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=861452;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 16, epoch: 17                       
steps:   8%|█▍               | 170/2000 [04:19<46:30,  1.52s/it, avr_loss=0.344]
epoch 18/200
2025-07-08 23:30:01 INFO     epoch is incremented.             ]8;id=75638;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=986018;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 17, epoch: 18                       
steps:   9%|█▌               | 180/2000 [04:34<46:10,  1.52s/it, avr_loss=0.371]
epoch 19/200
2025-07-08 23:30:16 INFO     epoch is incremented.             ]8;id=394681;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=167494;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 18, epoch: 19                       
steps:  10%|█▌               | 190/2000 [04:48<45:51,  1.52s/it, avr_loss=0.421]
epoch 20/200
2025-07-08 23:30:31 INFO     epoch is incremented.             ]8;id=50802;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=495147;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 19, epoch: 20                       
steps:  10%|█▋               | 200/2000 [05:03<45:31,  1.52s/it, avr_loss=0.403]2025-07-08 23:30:45 INFO                                  ]8;id=943205;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=84303;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=996514;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=267277;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 200                                      
                    INFO     prompt: ohwx woman in a     ]8;id=107762;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=296551;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=819666;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=606288;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=374977;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=999587;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=894391;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=170918;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=821991;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=340012;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 21/200
2025-07-08 23:30:48 INFO     epoch is incremented.             ]8;id=384758;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=954365;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 20, epoch: 21                       
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epoch 22/200
2025-07-08 23:31:02 INFO     epoch is incremented.             ]8;id=396347;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=241811;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 21, epoch: 22                       
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epoch 23/200
2025-07-08 23:31:17 INFO     epoch is incremented.             ]8;id=986559;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=81720;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 22, epoch: 23                       
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epoch 24/200
2025-07-08 23:31:32 INFO     epoch is incremented.             ]8;id=775337;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=688353;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 23, epoch: 24                       
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epoch 25/200
2025-07-08 23:31:47 INFO     epoch is incremented.             ]8;id=690915;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=956752;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 24, epoch: 25                       
steps:  12%|██▏              | 250/2000 [06:19<44:17,  1.52s/it, avr_loss=0.379]2025-07-08 23:32:02 INFO                                  ]8;id=882623;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=632751;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=672556;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=77333;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 250                                      
                    INFO     prompt: ohwx woman in a     ]8;id=417903;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=696267;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=337407;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=294669;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=790709;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=192877;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=818241;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=437234;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=365379;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=903041;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 26/200
2025-07-08 23:32:04 INFO     epoch is incremented.             ]8;id=518513;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=389617;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
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epoch 27/200
2025-07-08 23:32:19 INFO     epoch is incremented.             ]8;id=533839;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=215414;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 26, epoch: 27                       
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epoch 28/200
2025-07-08 23:32:33 INFO     epoch is incremented.             ]8;id=698577;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=592608;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 27, epoch: 28                       
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epoch 29/200
2025-07-08 23:32:48 INFO     epoch is incremented.             ]8;id=114655;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=536653;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 28, epoch: 29                       
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epoch 30/200
2025-07-08 23:33:03 INFO     epoch is incremented.             ]8;id=141211;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=650628;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 29, epoch: 30                       
steps:  15%|██▌              | 300/2000 [07:35<43:02,  1.52s/it, avr_loss=0.396]2025-07-08 23:33:18 INFO                                  ]8;id=431932;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=165138;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=845748;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=85552;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 300                                      
                    INFO     prompt: ohwx woman in a     ]8;id=222623;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=522244;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=64272;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=392436;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=171006;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=455306;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=290721;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=402890;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=606814;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=471754;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 31/200
2025-07-08 23:33:20 INFO     epoch is incremented.             ]8;id=86113;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=24321;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 30, epoch: 31                       
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epoch 32/200
2025-07-08 23:33:35 INFO     epoch is incremented.             ]8;id=90437;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=51514;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 31, epoch: 32                       
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epoch 33/200
2025-07-08 23:33:49 INFO     epoch is incremented.             ]8;id=102559;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=503277;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 32, epoch: 33                       
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epoch 34/200
2025-07-08 23:34:04 INFO     epoch is incremented.             ]8;id=413417;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=612945;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 33, epoch: 34                       
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epoch 35/200
2025-07-08 23:34:19 INFO     epoch is incremented.             ]8;id=977978;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=514410;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 34, epoch: 35                       
steps:  18%|██▉              | 350/2000 [08:51<41:47,  1.52s/it, avr_loss=0.424]2025-07-08 23:34:34 INFO                                  ]8;id=376053;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=435648;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=174833;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=366578;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 350                                      
                    INFO     prompt: ohwx woman in a     ]8;id=760951;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=809286;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=891703;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=851608;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=522521;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=675468;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=306147;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=324591;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=444157;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=611742;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 36/200
2025-07-08 23:34:36 INFO     epoch is incremented.             ]8;id=588082;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=981628;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 35, epoch: 36                       
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epoch 37/200
2025-07-08 23:34:51 INFO     epoch is incremented.             ]8;id=811740;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=300570;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 36, epoch: 37                       
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epoch 38/200
2025-07-08 23:35:06 INFO     epoch is incremented.             ]8;id=844683;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=761335;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 37, epoch: 38                       
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epoch 39/200
2025-07-08 23:35:20 INFO     epoch is incremented.             ]8;id=990416;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=9241;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 38, epoch: 39                       
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epoch 40/200
2025-07-08 23:35:35 INFO     epoch is incremented.             ]8;id=6661;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=311181;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 39, epoch: 40                       
steps:  20%|███▍             | 400/2000 [10:07<40:31,  1.52s/it, avr_loss=0.382]2025-07-08 23:35:50 INFO                                  ]8;id=604168;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=749647;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=235290;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=772685;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 400                                      
                    INFO     prompt: ohwx woman in a     ]8;id=9856;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=391225;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=111623;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=663246;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=861751;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=650922;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=188138;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=298613;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=965020;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=471808;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 41/200
2025-07-08 23:35:52 INFO     epoch is incremented.             ]8;id=995801;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=769690;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 40, epoch: 41                       
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epoch 42/200
2025-07-08 23:36:07 INFO     epoch is incremented.             ]8;id=634062;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=603144;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 41, epoch: 42                       
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epoch 43/200
2025-07-08 23:36:22 INFO     epoch is incremented.             ]8;id=912282;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=208429;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 42, epoch: 43                       
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epoch 44/200
2025-07-08 23:36:36 INFO     epoch is incremented.             ]8;id=920045;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=275217;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 43, epoch: 44                       
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epoch 45/200
2025-07-08 23:36:51 INFO     epoch is incremented.             ]8;id=508839;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=440090;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 44, epoch: 45                       
steps:  22%|███▊             | 450/2000 [11:23<39:15,  1.52s/it, avr_loss=0.358]2025-07-08 23:37:06 INFO                                  ]8;id=795830;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=331144;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=521915;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=685391;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 450                                      
                    INFO     prompt: ohwx woman in a     ]8;id=511398;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=76495;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=1411;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=180696;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=710962;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=140836;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=260217;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=953098;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=112276;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=723991;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 46/200
2025-07-08 23:37:08 INFO     epoch is incremented.             ]8;id=102540;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=70031;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 45, epoch: 46                       
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epoch 47/200
2025-07-08 23:37:23 INFO     epoch is incremented.             ]8;id=400480;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=239857;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 46, epoch: 47                       
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epoch 48/200
2025-07-08 23:37:38 INFO     epoch is incremented.             ]8;id=262657;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=869991;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 47, epoch: 48                       
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epoch 49/200
2025-07-08 23:37:52 INFO     epoch is incremented.             ]8;id=923518;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=736410;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 48, epoch: 49                       
steps:  24%|████▍             | 490/2000 [12:25<38:17,  1.52s/it, avr_loss=0.38]
epoch 50/200
2025-07-08 23:38:07 INFO     epoch is incremented.             ]8;id=667592;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=553032;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 49, epoch: 50                       
steps:  25%|████▎            | 500/2000 [12:40<38:00,  1.52s/it, avr_loss=0.385]2025-07-08 23:38:22 INFO                                  ]8;id=766721;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=947314;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=452702;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=787544;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 500                                      
                    INFO     prompt: ohwx woman in a     ]8;id=810938;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=884251;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=442496;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=63980;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=482720;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=582939;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=859432;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=171899;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=483598;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=59302;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 51/200
2025-07-08 23:38:24 INFO     epoch is incremented.             ]8;id=296290;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=575210;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 50, epoch: 51                       
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epoch 52/200
2025-07-08 23:38:39 INFO     epoch is incremented.             ]8;id=48395;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=541172;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 51, epoch: 52                       
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epoch 53/200
2025-07-08 23:38:54 INFO     epoch is incremented.             ]8;id=848574;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=167058;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 52, epoch: 53                       
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epoch 54/200
2025-07-08 23:39:09 INFO     epoch is incremented.             ]8;id=661839;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=475202;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 53, epoch: 54                       
steps:  27%|████▌            | 540/2000 [13:41<37:00,  1.52s/it, avr_loss=0.408]
epoch 55/200
2025-07-08 23:39:23 INFO     epoch is incremented.             ]8;id=222635;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=875210;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 54, epoch: 55                       
steps:  28%|████▋            | 550/2000 [13:56<36:44,  1.52s/it, avr_loss=0.363]2025-07-08 23:39:38 INFO                                  ]8;id=520552;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=477515;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=853678;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=281495;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 550                                      
                    INFO     prompt: ohwx woman in a     ]8;id=484311;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=127110;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=889056;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=861082;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=986358;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=37001;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=793663;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=286108;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=697545;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=593026;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 56/200
2025-07-08 23:39:40 INFO     epoch is incremented.             ]8;id=3116;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=938103;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 55, epoch: 56                       
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epoch 57/200
2025-07-08 23:39:55 INFO     epoch is incremented.             ]8;id=860716;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=786415;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 56, epoch: 57                       
steps:  28%|█████▍             | 570/2000 [14:27<36:17,  1.52s/it, avr_loss=0.4]
epoch 58/200
2025-07-08 23:40:10 INFO     epoch is incremented.             ]8;id=494163;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=847574;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 57, epoch: 58                       
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epoch 59/200
2025-07-08 23:40:25 INFO     epoch is incremented.             ]8;id=414957;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=684932;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 58, epoch: 59                       
steps:  30%|█████            | 590/2000 [14:57<35:44,  1.52s/it, avr_loss=0.354]
epoch 60/200
2025-07-08 23:40:39 INFO     epoch is incremented.             ]8;id=393044;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=251792;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 59, epoch: 60                       
steps:  30%|█████            | 600/2000 [15:12<35:28,  1.52s/it, avr_loss=0.382]2025-07-08 23:40:54 INFO                                  ]8;id=607279;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=180986;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=134008;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=165934;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 600                                      
                    INFO     prompt: ohwx woman in a     ]8;id=321012;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=814648;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=341119;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=981804;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=186409;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=679606;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=416820;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=337062;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=317573;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=314408;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 61/200
2025-07-08 23:40:56 INFO     epoch is incremented.             ]8;id=237815;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=775388;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 60, epoch: 61                       
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epoch 62/200
2025-07-08 23:41:11 INFO     epoch is incremented.             ]8;id=862534;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=840665;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 61, epoch: 62                       
steps:  31%|█████▎           | 620/2000 [15:43<35:00,  1.52s/it, avr_loss=0.389]
epoch 63/200
2025-07-08 23:41:26 INFO     epoch is incremented.             ]8;id=435013;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=811390;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 62, epoch: 63                       
steps:  32%|█████▎           | 630/2000 [15:58<34:44,  1.52s/it, avr_loss=0.397]
epoch 64/200
2025-07-08 23:41:41 INFO     epoch is incremented.             ]8;id=481835;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=314222;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 63, epoch: 64                       
steps:  32%|█████▍           | 640/2000 [16:13<34:28,  1.52s/it, avr_loss=0.407]
epoch 65/200
2025-07-08 23:41:55 INFO     epoch is incremented.             ]8;id=60235;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=604146;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 64, epoch: 65                       
steps:  32%|█████▌           | 650/2000 [16:28<34:12,  1.52s/it, avr_loss=0.433]2025-07-08 23:42:10 INFO                                  ]8;id=751256;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=56778;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=802473;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=452800;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 650                                      
                    INFO     prompt: ohwx woman in a     ]8;id=404835;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=81508;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=738383;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=704737;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=50759;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=950527;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=925247;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=121361;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=689826;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=869621;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 66/200
2025-07-08 23:42:12 INFO     epoch is incremented.             ]8;id=322519;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=408185;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 65, epoch: 66                       
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epoch 67/200
2025-07-08 23:42:27 INFO     epoch is incremented.             ]8;id=785949;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=26924;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 66, epoch: 67                       
steps:  34%|██████            | 670/2000 [16:59<33:44,  1.52s/it, avr_loss=0.34]
epoch 68/200
2025-07-08 23:42:42 INFO     epoch is incremented.             ]8;id=658375;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=876202;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 67, epoch: 68                       
steps:  34%|█████▊           | 680/2000 [17:14<33:28,  1.52s/it, avr_loss=0.392]
epoch 69/200
2025-07-08 23:42:57 INFO     epoch is incremented.             ]8;id=180833;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=13598;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 68, epoch: 69                       
steps:  34%|█████▊           | 690/2000 [17:29<33:12,  1.52s/it, avr_loss=0.372]
epoch 70/200
2025-07-08 23:43:11 INFO     epoch is incremented.             ]8;id=225536;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=452834;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 69, epoch: 70                       
steps:  35%|█████▉           | 700/2000 [17:44<32:56,  1.52s/it, avr_loss=0.388]2025-07-08 23:43:26 INFO                                  ]8;id=943862;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=753234;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=905601;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=658372;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 700                                      
                    INFO     prompt: ohwx woman in a     ]8;id=244854;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=562886;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=754023;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=709816;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=775021;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=704876;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=645663;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=83971;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=893404;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=159478;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 71/200
2025-07-08 23:43:28 INFO     epoch is incremented.             ]8;id=744034;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=873854;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 70, epoch: 71                       
steps:  36%|██████           | 710/2000 [18:01<32:44,  1.52s/it, avr_loss=0.351]
epoch 72/200
2025-07-08 23:43:43 INFO     epoch is incremented.             ]8;id=411622;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=306294;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 71, epoch: 72                       
steps:  36%|██████           | 720/2000 [18:15<32:28,  1.52s/it, avr_loss=0.349]
epoch 73/200
2025-07-08 23:43:58 INFO     epoch is incremented.             ]8;id=650878;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=199070;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 72, epoch: 73                       
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epoch 74/200
2025-07-08 23:44:13 INFO     epoch is incremented.             ]8;id=507238;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=516743;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 73, epoch: 74                       
steps:  37%|██████▎          | 740/2000 [18:45<31:56,  1.52s/it, avr_loss=0.342]
epoch 75/200
2025-07-08 23:44:27 INFO     epoch is incremented.             ]8;id=259065;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=924153;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 74, epoch: 75                       
steps:  38%|██████▍          | 750/2000 [19:00<31:40,  1.52s/it, avr_loss=0.405]2025-07-08 23:44:42 INFO                                  ]8;id=153769;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=558536;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=936205;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=749472;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 750                                      
                    INFO     prompt: ohwx woman in a     ]8;id=876367;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=414563;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=419122;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=338952;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=512579;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=836734;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=306159;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=382051;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=254397;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=956194;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 76/200
2025-07-08 23:44:44 INFO     epoch is incremented.             ]8;id=535668;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=993697;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 75, epoch: 76                       
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epoch 77/200
2025-07-08 23:44:59 INFO     epoch is incremented.             ]8;id=35380;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=686335;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 76, epoch: 77                       
steps:  38%|██████▌          | 770/2000 [19:31<31:12,  1.52s/it, avr_loss=0.413]
epoch 78/200
2025-07-08 23:45:14 INFO     epoch is incremented.             ]8;id=378953;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=560609;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 77, epoch: 78                       
steps:  39%|██████▋          | 780/2000 [19:46<30:56,  1.52s/it, avr_loss=0.349]
epoch 79/200
2025-07-08 23:45:29 INFO     epoch is incremented.             ]8;id=651274;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=447328;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 78, epoch: 79                       
steps:  40%|██████▋          | 790/2000 [20:01<30:40,  1.52s/it, avr_loss=0.334]
epoch 80/200
2025-07-08 23:45:43 INFO     epoch is incremented.             ]8;id=320240;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=84293;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 79, epoch: 80                       
steps:  40%|███████▏          | 800/2000 [20:16<30:24,  1.52s/it, avr_loss=0.35]2025-07-08 23:45:58 INFO                                  ]8;id=654074;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=331196;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=394048;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=706577;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 800                                      
                    INFO     prompt: ohwx woman in a     ]8;id=322360;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=887017;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=993077;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=810969;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=451455;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=112837;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=491225;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=334402;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=467636;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=639066;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  40%|██████▊          | 800/2000 [20:18<30:27,  1.52s/it, avr_loss=0.378]
epoch 81/200
2025-07-08 23:46:00 INFO     epoch is incremented.             ]8;id=375228;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=39762;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 80, epoch: 81                       
steps:  40%|██████▉          | 810/2000 [20:33<30:11,  1.52s/it, avr_loss=0.319]
epoch 82/200
2025-07-08 23:46:15 INFO     epoch is incremented.             ]8;id=332152;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=538117;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 81, epoch: 82                       
steps:  41%|██████▉          | 820/2000 [20:47<29:55,  1.52s/it, avr_loss=0.415]
epoch 83/200
2025-07-08 23:46:30 INFO     epoch is incremented.             ]8;id=175731;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=483242;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 82, epoch: 83                       
steps:  42%|███████▍          | 830/2000 [21:02<29:39,  1.52s/it, avr_loss=0.33]
epoch 84/200
2025-07-08 23:46:45 INFO     epoch is incremented.             ]8;id=681456;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=449580;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 83, epoch: 84                       
steps:  42%|███████▌          | 840/2000 [21:17<29:24,  1.52s/it, avr_loss=0.33]
epoch 85/200
2025-07-08 23:46:59 INFO     epoch is incremented.             ]8;id=399200;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=672264;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 84, epoch: 85                       
steps:  42%|████████           | 850/2000 [21:32<29:08,  1.52s/it, avr_loss=0.4]2025-07-08 23:47:14 INFO                                  ]8;id=102122;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=963385;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=712684;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=724632;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 850                                      
                    INFO     prompt: ohwx woman in a     ]8;id=95468;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=114363;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=817470;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=267079;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=176915;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=26615;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=266560;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=749137;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=961395;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=340409;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  42%|███████▋          | 850/2000 [21:34<29:11,  1.52s/it, avr_loss=0.39]
epoch 86/200
2025-07-08 23:47:16 INFO     epoch is incremented.             ]8;id=331526;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=368169;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 85, epoch: 86                       
steps:  43%|███████▎         | 860/2000 [21:49<28:55,  1.52s/it, avr_loss=0.423]
epoch 87/200
2025-07-08 23:47:31 INFO     epoch is incremented.             ]8;id=172856;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=626520;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 86, epoch: 87                       
steps:  44%|███████▍         | 870/2000 [22:03<28:39,  1.52s/it, avr_loss=0.405]
epoch 88/200
2025-07-08 23:47:46 INFO     epoch is incremented.             ]8;id=988128;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=957671;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 87, epoch: 88                       
steps:  44%|███████▍         | 880/2000 [22:18<28:23,  1.52s/it, avr_loss=0.434]
epoch 89/200
2025-07-08 23:48:01 INFO     epoch is incremented.             ]8;id=922122;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=769099;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 88, epoch: 89                       
steps:  44%|████████          | 890/2000 [22:33<28:08,  1.52s/it, avr_loss=0.39]
epoch 90/200
2025-07-08 23:48:15 INFO     epoch is incremented.             ]8;id=747371;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=555085;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 89, epoch: 90                       
steps:  45%|███████▋         | 900/2000 [22:48<27:52,  1.52s/it, avr_loss=0.433]2025-07-08 23:48:30 INFO                                  ]8;id=649928;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=286814;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=890159;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=963135;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 900                                      
                    INFO     prompt: ohwx woman in a     ]8;id=148269;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=89977;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=719837;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=827224;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=502406;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=738957;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=612678;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=765696;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=56294;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=887965;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  45%|████████          | 900/2000 [22:50<27:55,  1.52s/it, avr_loss=0.44]
epoch 91/200
2025-07-08 23:48:32 INFO     epoch is incremented.             ]8;id=243491;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=135404;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 90, epoch: 91                       
steps:  46%|███████▋         | 910/2000 [23:05<27:39,  1.52s/it, avr_loss=0.362]
epoch 92/200
2025-07-08 23:48:47 INFO     epoch is incremented.             ]8;id=317463;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=413370;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 91, epoch: 92                       
steps:  46%|███████▊         | 920/2000 [23:20<27:23,  1.52s/it, avr_loss=0.382]
epoch 93/200
2025-07-08 23:49:02 INFO     epoch is incremented.             ]8;id=68658;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=483493;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 92, epoch: 93                       
steps:  46%|███████▉         | 930/2000 [23:34<27:07,  1.52s/it, avr_loss=0.364]
epoch 94/200
2025-07-08 23:49:17 INFO     epoch is incremented.             ]8;id=448411;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=886408;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 93, epoch: 94                       
steps:  47%|███████▉         | 940/2000 [23:49<26:52,  1.52s/it, avr_loss=0.442]
epoch 95/200
2025-07-08 23:49:31 INFO     epoch is incremented.             ]8;id=972906;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=852847;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 94, epoch: 95                       
steps:  48%|████████         | 950/2000 [24:04<26:36,  1.52s/it, avr_loss=0.388]2025-07-08 23:49:46 INFO                                  ]8;id=882744;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=515180;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=618084;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=544457;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 950                                      
                    INFO     prompt: ohwx woman in a     ]8;id=854653;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=471121;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=756531;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=801316;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=685014;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=27940;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=237373;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=852694;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=707331;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=710072;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  48%|████████         | 950/2000 [24:06<26:38,  1.52s/it, avr_loss=0.382]
epoch 96/200
2025-07-08 23:49:49 INFO     epoch is incremented.             ]8;id=252623;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=273881;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 95, epoch: 96                       
steps:  48%|████████▏        | 960/2000 [24:21<26:23,  1.52s/it, avr_loss=0.458]
epoch 97/200
2025-07-08 23:50:03 INFO     epoch is incremented.             ]8;id=252791;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=504224;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 96, epoch: 97                       
steps:  48%|████████▏        | 970/2000 [24:36<26:07,  1.52s/it, avr_loss=0.337]
epoch 98/200
2025-07-08 23:50:18 INFO     epoch is incremented.             ]8;id=569922;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=291666;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 97, epoch: 98                       
steps:  49%|████████▎        | 980/2000 [24:50<25:51,  1.52s/it, avr_loss=0.374]
epoch 99/200
2025-07-08 23:50:33 INFO     epoch is incremented.             ]8;id=375328;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=184881;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 98, epoch: 99                       
steps:  50%|████████▍        | 990/2000 [25:05<25:36,  1.52s/it, avr_loss=0.361]
epoch 100/200
2025-07-08 23:50:48 INFO     epoch is incremented.             ]8;id=336252;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=505717;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 99, epoch: 100                      
steps:  50%|████████        | 1000/2000 [25:20<25:20,  1.52s/it, avr_loss=0.389]2025-07-08 23:51:02 INFO                                  ]8;id=26991;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=773768;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=358195;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=953639;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1000                                     
                    INFO     prompt: ohwx woman in a     ]8;id=432310;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=32741;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=587675;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=338713;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=116245;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=736284;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=440093;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=416434;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=23162;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=160638;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  50%|████████        | 1000/2000 [25:22<25:22,  1.52s/it, avr_loss=0.377]
epoch 101/200
2025-07-08 23:51:05 INFO     epoch is incremented.             ]8;id=59482;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=882476;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 100, epoch: 101                     
steps:  50%|████████▌        | 1010/2000 [25:37<25:06,  1.52s/it, avr_loss=0.44]
epoch 102/200
2025-07-08 23:51:19 INFO     epoch is incremented.             ]8;id=307915;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=856484;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 101, epoch: 102                     
steps:  51%|████████▏       | 1020/2000 [25:52<24:51,  1.52s/it, avr_loss=0.454]
epoch 103/200
2025-07-08 23:51:34 INFO     epoch is incremented.             ]8;id=932338;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=635495;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 102, epoch: 103                     
steps:  52%|████████▏       | 1030/2000 [26:06<24:35,  1.52s/it, avr_loss=0.388]
epoch 104/200
2025-07-08 23:51:49 INFO     epoch is incremented.             ]8;id=188078;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=740348;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 103, epoch: 104                     
steps:  52%|████████▎       | 1040/2000 [26:21<24:20,  1.52s/it, avr_loss=0.411]
epoch 105/200
2025-07-08 23:52:04 INFO     epoch is incremented.             ]8;id=142157;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=68316;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 104, epoch: 105                     
steps:  52%|████████▍       | 1050/2000 [26:36<24:04,  1.52s/it, avr_loss=0.418]2025-07-08 23:52:18 INFO                                  ]8;id=602403;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=82332;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=135722;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=621101;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1050                                     
                    INFO     prompt: ohwx woman in a     ]8;id=614302;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=576392;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=616636;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=49126;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=504962;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=114150;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=429801;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=289469;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=675776;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=963018;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 106/200
2025-07-08 23:52:21 INFO     epoch is incremented.             ]8;id=299297;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=70282;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 105, epoch: 106                     
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epoch 107/200
2025-07-08 23:52:35 INFO     epoch is incremented.             ]8;id=511809;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=982131;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 106, epoch: 107                     
steps:  54%|████████▌       | 1070/2000 [27:08<23:35,  1.52s/it, avr_loss=0.357]
epoch 108/200
2025-07-08 23:52:50 INFO     epoch is incremented.             ]8;id=86249;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=579546;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 107, epoch: 108                     
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epoch 109/200
2025-07-08 23:53:05 INFO     epoch is incremented.             ]8;id=591435;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=415400;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 108, epoch: 109                     
steps:  55%|████████▋       | 1090/2000 [27:37<23:04,  1.52s/it, avr_loss=0.428]
epoch 110/200
2025-07-08 23:53:20 INFO     epoch is incremented.             ]8;id=71564;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=384360;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 109, epoch: 110                     
steps:  55%|████████▊       | 1100/2000 [27:52<22:48,  1.52s/it, avr_loss=0.342]2025-07-08 23:53:34 INFO                                  ]8;id=302896;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=425779;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=493311;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=774748;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1100                                     
                    INFO     prompt: ohwx woman in a     ]8;id=85970;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=837492;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=302907;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=737879;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=108924;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=823402;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=176457;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=150481;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=957108;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=592956;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 111/200
2025-07-08 23:53:37 INFO     epoch is incremented.             ]8;id=370337;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=258247;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 110, epoch: 111                     
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epoch 112/200
2025-07-08 23:53:51 INFO     epoch is incremented.             ]8;id=765279;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=288231;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 111, epoch: 112                     
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epoch 113/200
2025-07-08 23:54:06 INFO     epoch is incremented.             ]8;id=147753;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=821453;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 112, epoch: 113                     
steps:  56%|█████████       | 1130/2000 [28:39<22:03,  1.52s/it, avr_loss=0.418]
epoch 114/200
2025-07-08 23:54:21 INFO     epoch is incremented.             ]8;id=927051;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=802642;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 113, epoch: 114                     
steps:  57%|█████████       | 1140/2000 [28:53<21:48,  1.52s/it, avr_loss=0.355]
epoch 115/200
2025-07-08 23:54:36 INFO     epoch is incremented.             ]8;id=436556;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=685157;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 114, epoch: 115                     
steps:  57%|█████████▏      | 1150/2000 [29:08<21:32,  1.52s/it, avr_loss=0.402]2025-07-08 23:54:50 INFO                                  ]8;id=885441;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=503589;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=780078;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=856909;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1150                                     
                    INFO     prompt: ohwx woman in a     ]8;id=99485;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=160642;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=108012;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=29065;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=94077;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=321808;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=561018;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=638947;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=51546;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=99371;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 116/200
2025-07-08 23:54:53 INFO     epoch is incremented.             ]8;id=242570;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=574115;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 115, epoch: 116                     
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epoch 117/200
2025-07-08 23:55:07 INFO     epoch is incremented.             ]8;id=324352;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=49995;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 116, epoch: 117                     
steps:  58%|█████████▎      | 1170/2000 [29:40<21:02,  1.52s/it, avr_loss=0.432]
epoch 118/200
2025-07-08 23:55:22 INFO     epoch is incremented.             ]8;id=185628;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=370714;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 117, epoch: 118                     
steps:  59%|██████████       | 1180/2000 [29:55<20:47,  1.52s/it, avr_loss=0.39]
epoch 119/200
2025-07-08 23:55:37 INFO     epoch is incremented.             ]8;id=746573;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=650241;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 118, epoch: 119                     
steps:  60%|█████████▌      | 1190/2000 [30:09<20:31,  1.52s/it, avr_loss=0.413]
epoch 120/200
2025-07-08 23:55:52 INFO     epoch is incremented.             ]8;id=504403;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=849999;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 119, epoch: 120                     
steps:  60%|█████████▌      | 1200/2000 [30:24<20:16,  1.52s/it, avr_loss=0.363]2025-07-08 23:56:07 INFO                                  ]8;id=565094;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=868846;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=459846;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=376998;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1200                                     
                    INFO     prompt: ohwx woman in a     ]8;id=839039;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=179857;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=853966;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=761158;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=483892;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=434064;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=122403;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=606202;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=427997;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=595005;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 121/200
2025-07-08 23:56:09 INFO     epoch is incremented.             ]8;id=777442;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=250254;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 120, epoch: 121                     
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epoch 122/200
2025-07-08 23:56:24 INFO     epoch is incremented.             ]8;id=552107;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=41699;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 121, epoch: 122                     
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epoch 123/200
2025-07-08 23:56:38 INFO     epoch is incremented.             ]8;id=720330;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=645619;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 122, epoch: 123                     
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epoch 124/200
2025-07-08 23:56:53 INFO     epoch is incremented.             ]8;id=711314;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=671952;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 123, epoch: 124                     
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epoch 125/200
2025-07-08 23:57:08 INFO     epoch is incremented.             ]8;id=363746;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=319935;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 124, epoch: 125                     
steps:  62%|██████████      | 1250/2000 [31:40<19:00,  1.52s/it, avr_loss=0.349]2025-07-08 23:57:22 INFO                                  ]8;id=548608;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=449550;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=518088;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=839024;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1250                                     
                    INFO     prompt: ohwx woman in a     ]8;id=496494;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=438143;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=116232;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=602997;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=588768;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=799597;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=644403;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=175508;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=16152;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=437503;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 126/200
2025-07-08 23:57:25 INFO     epoch is incremented.             ]8;id=661221;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=593934;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 125, epoch: 126                     
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epoch 127/200
2025-07-08 23:57:40 INFO     epoch is incremented.             ]8;id=330026;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=181923;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 126, epoch: 127                     
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epoch 128/200
2025-07-08 23:57:54 INFO     epoch is incremented.             ]8;id=72499;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=262477;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 127, epoch: 128                     
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epoch 129/200
2025-07-08 23:58:09 INFO     epoch is incremented.             ]8;id=946231;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=674716;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 128, epoch: 129                     
steps:  64%|██████████▎     | 1290/2000 [32:41<17:59,  1.52s/it, avr_loss=0.326]
epoch 130/200
2025-07-08 23:58:24 INFO     epoch is incremented.             ]8;id=85273;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=388181;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 129, epoch: 130                     
steps:  65%|██████████▍     | 1300/2000 [32:56<17:44,  1.52s/it, avr_loss=0.364]2025-07-08 23:58:39 INFO                                  ]8;id=291851;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=844090;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=410101;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=606803;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1300                                     
                    INFO     prompt: ohwx woman in a     ]8;id=736121;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=165563;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=574727;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=651184;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=846368;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=862447;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=53774;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=759421;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=513540;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=33519;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 131/200
2025-07-08 23:58:41 INFO     epoch is incremented.             ]8;id=320265;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=969191;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 130, epoch: 131                     
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epoch 132/200
2025-07-08 23:58:56 INFO     epoch is incremented.             ]8;id=810082;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=301051;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 131, epoch: 132                     
steps:  66%|██████████▌     | 1320/2000 [33:28<17:14,  1.52s/it, avr_loss=0.408]
epoch 133/200
2025-07-08 23:59:10 INFO     epoch is incremented.             ]8;id=991965;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=742610;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 132, epoch: 133                     
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epoch 134/200
2025-07-08 23:59:25 INFO     epoch is incremented.             ]8;id=752951;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=963032;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 133, epoch: 134                     
steps:  67%|██████████▋     | 1340/2000 [33:57<16:43,  1.52s/it, avr_loss=0.444]
epoch 135/200
2025-07-08 23:59:40 INFO     epoch is incremented.             ]8;id=93398;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=793701;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 134, epoch: 135                     
steps:  68%|██████████▊     | 1350/2000 [34:12<16:28,  1.52s/it, avr_loss=0.367]2025-07-08 23:59:55 INFO                                  ]8;id=488520;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=125212;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=203042;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=180403;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1350                                     
                    INFO     prompt: ohwx woman in a     ]8;id=229130;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=228573;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=45378;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=134070;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=417898;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=602590;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=649990;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=193630;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=680767;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=574293;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  68%|██████████▊     | 1350/2000 [34:14<16:29,  1.52s/it, avr_loss=0.346]
epoch 136/200
2025-07-08 23:59:57 INFO     epoch is incremented.             ]8;id=593098;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=69091;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 135, epoch: 136                     
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epoch 137/200
2025-07-09 00:00:12 INFO     epoch is incremented.             ]8;id=891965;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=744029;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 136, epoch: 137                     
steps:  68%|██████████▉     | 1370/2000 [34:44<15:58,  1.52s/it, avr_loss=0.326]
epoch 138/200
2025-07-09 00:00:27 INFO     epoch is incremented.             ]8;id=143447;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=91117;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 137, epoch: 138                     
steps:  69%|███████████     | 1380/2000 [34:59<15:43,  1.52s/it, avr_loss=0.401]
epoch 139/200
2025-07-09 00:00:41 INFO     epoch is incremented.             ]8;id=875997;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=685329;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 138, epoch: 139                     
steps:  70%|███████████     | 1390/2000 [35:14<15:27,  1.52s/it, avr_loss=0.375]
epoch 140/200
2025-07-09 00:00:56 INFO     epoch is incremented.             ]8;id=579279;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=286806;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 139, epoch: 140                     
steps:  70%|███████████▏    | 1400/2000 [35:29<15:12,  1.52s/it, avr_loss=0.393]2025-07-09 00:01:11 INFO                                  ]8;id=391179;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=552283;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=421856;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=140245;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1400                                     
                    INFO     prompt: ohwx woman in a     ]8;id=445463;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=509581;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=320894;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=713675;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=955074;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=835020;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=958282;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=687653;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=239997;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=233250;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 141/200
2025-07-09 00:01:13 INFO     epoch is incremented.             ]8;id=687571;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=300689;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 140, epoch: 141                     
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epoch 142/200
2025-07-09 00:01:28 INFO     epoch is incremented.             ]8;id=744406;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=704320;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 141, epoch: 142                     
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epoch 143/200
2025-07-09 00:01:43 INFO     epoch is incremented.             ]8;id=449717;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=122768;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 142, epoch: 143                     
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epoch 144/200
2025-07-09 00:01:57 INFO     epoch is incremented.             ]8;id=766563;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=793391;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 143, epoch: 144                     
steps:  72%|███████████▌    | 1440/2000 [36:30<14:11,  1.52s/it, avr_loss=0.388]
epoch 145/200
2025-07-09 00:02:12 INFO     epoch is incremented.             ]8;id=174811;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=884483;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 144, epoch: 145                     
steps:  72%|███████████▌    | 1450/2000 [36:45<13:56,  1.52s/it, avr_loss=0.357]2025-07-09 00:02:27 INFO                                  ]8;id=417767;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=209720;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=787048;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=830307;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1450                                     
                    INFO     prompt: ohwx woman in a     ]8;id=691328;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=357546;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=115806;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=865655;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=467113;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=994779;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=442687;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=673785;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=28436;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=524787;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 146/200
2025-07-09 00:02:29 INFO     epoch is incremented.             ]8;id=696402;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=518602;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 145, epoch: 146                     
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epoch 147/200
2025-07-09 00:02:44 INFO     epoch is incremented.             ]8;id=217455;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=977299;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 146, epoch: 147                     
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epoch 148/200
2025-07-09 00:02:59 INFO     epoch is incremented.             ]8;id=343749;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=847890;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 147, epoch: 148                     
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epoch 149/200
2025-07-09 00:03:13 INFO     epoch is incremented.             ]8;id=512169;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=757395;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 148, epoch: 149                     
steps:  74%|███████████▉    | 1490/2000 [37:46<12:55,  1.52s/it, avr_loss=0.364]
epoch 150/200
2025-07-09 00:03:28 INFO     epoch is incremented.             ]8;id=186268;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=725882;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 149, epoch: 150                     
steps:  75%|████████████    | 1500/2000 [38:01<12:40,  1.52s/it, avr_loss=0.352]2025-07-09 00:03:43 INFO                                  ]8;id=804303;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=651464;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=72882;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=866607;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1500                                     
                    INFO     prompt: ohwx woman in a     ]8;id=73857;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=590864;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=969015;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=264421;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=789465;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=444295;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=936382;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=342953;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=667163;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=221431;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 151/200
2025-07-09 00:03:45 INFO     epoch is incremented.             ]8;id=14826;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=719531;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 150, epoch: 151                     
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epoch 152/200
2025-07-09 00:04:00 INFO     epoch is incremented.             ]8;id=592642;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=803956;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 151, epoch: 152                     
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epoch 153/200
2025-07-09 00:04:15 INFO     epoch is incremented.             ]8;id=830570;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=461799;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 152, epoch: 153                     
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epoch 154/200
2025-07-09 00:04:30 INFO     epoch is incremented.             ]8;id=397635;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=722251;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 153, epoch: 154                     
steps:  77%|████████████▎   | 1540/2000 [39:02<11:39,  1.52s/it, avr_loss=0.369]
epoch 155/200
2025-07-09 00:04:44 INFO     epoch is incremented.             ]8;id=118740;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=747709;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 154, epoch: 155                     
steps:  78%|████████████▍   | 1550/2000 [39:17<11:24,  1.52s/it, avr_loss=0.382]2025-07-09 00:04:59 INFO                                  ]8;id=74880;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=967122;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=451923;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=87909;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1550                                     
                    INFO     prompt: ohwx woman in a     ]8;id=852199;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=587325;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=428285;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=872940;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=900432;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=646780;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=305587;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=268897;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=556288;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=983462;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 156/200
2025-07-09 00:05:01 INFO     epoch is incremented.             ]8;id=733678;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=767259;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 155, epoch: 156                     
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epoch 157/200
2025-07-09 00:05:16 INFO     epoch is incremented.             ]8;id=210947;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=861016;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 156, epoch: 157                     
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epoch 158/200
2025-07-09 00:05:31 INFO     epoch is incremented.             ]8;id=201157;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=78990;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 157, epoch: 158                     
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epoch 159/200
2025-07-09 00:05:46 INFO     epoch is incremented.             ]8;id=739159;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=864349;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 158, epoch: 159                     
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epoch 160/200
2025-07-09 00:06:00 INFO     epoch is incremented.             ]8;id=254521;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=305893;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 159, epoch: 160                     
steps:  80%|█████████████▌   | 1600/2000 [40:33<10:08,  1.52s/it, avr_loss=0.41]2025-07-09 00:06:15 INFO                                  ]8;id=93114;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=578508;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=619965;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=684972;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1600                                     
                    INFO     prompt: ohwx woman in a     ]8;id=176148;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=31117;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=313691;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=773119;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=18806;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=557613;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=530889;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=598862;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=941417;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=98918;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 161/200
2025-07-09 00:06:17 INFO     epoch is incremented.             ]8;id=421113;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=294450;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 160, epoch: 161                     
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epoch 162/200
2025-07-09 00:06:32 INFO     epoch is incremented.             ]8;id=962591;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=257490;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 161, epoch: 162                     
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epoch 163/200
2025-07-09 00:06:47 INFO     epoch is incremented.             ]8;id=941578;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=92177;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 162, epoch: 163                     
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epoch 164/200
2025-07-09 00:07:02 INFO     epoch is incremented.             ]8;id=82436;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=803453;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 163, epoch: 164                     
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epoch 165/200
2025-07-09 00:07:16 INFO     epoch is incremented.             ]8;id=200659;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=979716;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 164, epoch: 165                     
steps:  82%|█████████████▏  | 1650/2000 [41:49<08:52,  1.52s/it, avr_loss=0.342]2025-07-09 00:07:31 INFO                                  ]8;id=494058;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=893834;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=426626;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=854519;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1650                                     
                    INFO     prompt: ohwx woman in a     ]8;id=244765;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=450856;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=853407;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=202214;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=806242;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=539938;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=926932;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=270796;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=919175;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=994446;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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epoch 166/200
2025-07-09 00:07:33 INFO     epoch is incremented.             ]8;id=275036;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=579624;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 165, epoch: 166                     
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epoch 167/200
2025-07-09 00:07:48 INFO     epoch is incremented.             ]8;id=979783;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=400277;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 166, epoch: 167                     
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epoch 168/200
2025-07-09 00:08:03 INFO     epoch is incremented.             ]8;id=367176;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=872165;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 167, epoch: 168                     
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epoch 169/200
2025-07-09 00:08:18 INFO     epoch is incremented.             ]8;id=686667;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=215035;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 168, epoch: 169                     
steps:  84%|█████████████▌  | 1690/2000 [42:50<07:51,  1.52s/it, avr_loss=0.339]
epoch 170/200
2025-07-09 00:08:33 INFO     epoch is incremented.             ]8;id=241061;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=40738;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 169, epoch: 170                     
steps:  85%|█████████████▌  | 1700/2000 [43:05<07:36,  1.52s/it, avr_loss=0.395]2025-07-09 00:08:47 INFO                                  ]8;id=773294;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=16144;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=679504;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=170682;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 1700                                     
                    INFO     prompt: ohwx woman in a     ]8;id=362372;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=858090;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             sophisticated winter                               
                             ensemble: wool coat in                             
                             burgundy, matching beret,                          
                             cashmere turtleneck, plaid                         
                             wool skirt below knees,                            
                             leather gloves, classic ice                        
                             skates, Italian wool scarf,                        
                             city plaza setting with                            
                             snow, twilight atmosphere                          
                             with twinkling lights                              
                    INFO     height: 512                 ]8;id=715935;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=869876;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=484434;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=545983;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=253699;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=893900;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=51453;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=261266;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights
Encoding prompt: ohwx woman in a sophisticated winter ensemble: wool coat in burgundy, matching beret, cashmere turtleneck, plaid wool skirt below knees, leather gloves, classic ice skates, Italian wool scarf, city plaza setting with snow, twilight atmosphere with twinkling lights

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steps:  85%|█████████████▌  | 1700/2000 [43:07<07:36,  1.52s/it, avr_loss=0.413]
epoch 171/200
2025-07-09 00:08:50 INFO     epoch is incremented.             ]8;id=556006;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=856464;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 170, epoch: 171                     
steps:  85%|█████████████▋  | 1705/2000 [43:15<07:29,  1.52s/it, avr_loss=0.371]00:08:57-877830 INFO     The running process has been terminated.               
00:08:58-682282 INFO     Training has ended.                                    
00:12:29-717499 INFO     Start training Dreambooth...                           
00:12:29-720806 INFO     Validating lr scheduler arguments...                   
00:12:29-722940 INFO     Validating optimizer arguments...                      
00:12:29-725122 INFO     Validating /kaggle/working/kohya_ss/training_data/log  
                         existence and writability... SUCCESS                   
00:12:29-727468 INFO     Validating /kaggle/working/kohya_ss/training_data/model
                         existence and writability... SUCCESS                   
00:12:29-729770 INFO     Validating                                             
                         /kaggle/working/kohya_ss/flux1-dev.safetensors         
                         existence... SUCCESS                                   
00:12:29-732183 INFO     Validating /kaggle/working/kohya_ss/training_data/img  
                         existence... SUCCESS                                   
00:12:29-734638 INFO     Error: '.ipynb_checkpoints' does not contain an        
                         underscore, skipping...                                
00:12:29-736867 INFO     Folder 1_ohwx woman: 1 repeats found                   
00:12:29-739053 INFO     Folder 1_ohwx woman: 10 images found                   
00:12:29-741018 INFO     Folder 1_ohwx woman: 10 * 1 = 10 steps                 
00:12:29-743031 INFO     Regularization factor: 1                               
00:12:29-745083 INFO     Total steps: 10                                        
00:12:29-746953 INFO     Train batch size: 1                                    
00:12:29-748785 INFO     Gradient accumulation steps: 1                         
00:12:29-752659 INFO     Epoch: 200                                             
00:12:29-754671 INFO     max_train_steps (10 / 1 / 1 * 200 * 1) = 2000          
00:12:29-757077 INFO     lr_warmup_steps = 0                                    
00:12:29-762904 INFO     Saving training config to                              
                         /kaggle/working/kohya_ss/training_data/model/test_20250
                         709-001229.json...                                     
00:12:29-766729 INFO     Executing command: /usr/local/bin/accelerate launch    
                         --dynamo_backend no --dynamo_mode default              
                         --mixed_precision bf16 --num_processes 1 --num_machines
                         1 --num_cpu_threads_per_process 2                      
                         /kohya_ss/kohya_ss/sd-scripts/flux_train.py            
                         --config_file                                          
                         /kaggle/working/kohya_ss/training_data/model/config_dre
                         ambooth-20250709-001229.toml                           
ipex flag is deprecated, will be removed in Accelerate v1.10. From 2.7.0, PyTorch has all needed optimizations for Intel CPU and XPU.
2025-07-09 00:12:40 INFO     Loading settings from            ]8;id=968034;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=498149;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4651\4651]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/model/config_dreambooth-2                   
                             0250709-001229.toml...                             
2025-07-09 00:12:40 INFO     Using DreamBooth method.          ]8;id=342071;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=997011;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#115\115]8;;\
                    WARNING  ignore directory without repeats ]8;id=816948;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=357542;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#613\613]8;;\
                             /                                                  
                             繰り返し回数のないディレクトリを                   
                             無視します: .ipynb_checkpoints                     
                    INFO     prepare images.                  ]8;id=903429;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=134972;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2072\2072]8;;\
                    INFO     get image size from name of      ]8;id=231927;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=133892;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1965\1965]8;;\
                             cache files                                        
100%|███████████████████████████████████████| 10/10 [00:00<00:00, 137068.76it/s]
                    INFO     set image size from cache files: ]8;id=84384;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=421768;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1995\1995]8;;\
                             10/10                                              
                    INFO     found directory                  ]8;id=474195;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=155254;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2019\2019]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/img/1_ohwx woman contains                   
                             10 image files                                     
read caption: 100%|██████████████████████████| 10/10 [00:00<00:00, 98457.84it/s]
                    WARNING  No caption file found for 10     ]8;id=258713;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=134721;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2050\2050]8;;\
                             images. Training will continue                     
                             without captions for these                         
                             images. If class token exists,                     
                             it will be used. /                                 
                             10枚の画像にキャプションファイル                   
                             が見つかりませんでした。これらの                   
                             画像についてはキャプションなしで                   
                             学習を続行します。class                            
                             tokenが存在する場合はそれを使い                    
                             ます。                                             
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=539720;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=126930;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543397075_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=596062;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=40721;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543589299_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=600161;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=646714;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681543625143_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=810369;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=885597;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681551853828_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=178954;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=5121;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681585397843_36808                   
                             84077.jpg                                          
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=187681;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=380613;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2055\2055]8;;\
                             g_data/img/1_ohwx                                  
                             woman/anupamaparameswaran96_1751                   
                             774400_3670085681585415928_36808                   
                             84077.jpg... and 5 more                            
                    INFO     10 train images with repeats.    ]8;id=507541;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=664284;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2116\2116]8;;\
                    INFO     0 reg images with repeats.       ]8;id=591647;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=215743;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2120\2120]8;;\
                    WARNING  no regularization images /       ]8;id=583849;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=905880;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2125\2125]8;;\
                             正則化画像が見つかりませんでした                   
                    INFO     [Dataset 0]                      ]8;id=218910;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=796297;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#580\580]8;;\
                               batch_size: 1                                    
                               resolution: (1024, 1024)                         
                               resize_interpolation: None                       
                               enable_bucket: True                              
                               min_bucket_reso: 256                             
                               max_bucket_reso: 2048                            
                               bucket_reso_steps: 64                            
                               bucket_no_upscale: True                          
                                                                                
                               [Subset 0 of Dataset 0]                          
                                 image_dir:                                     
                             "/kaggle/working/kohya_ss/traini                   
                             ng_data/img/1_ohwx woman"                          
                                 image_count: 10                                
                                 num_repeats: 1                                 
                                 shuffle_caption: False                         
                                 keep_tokens: 0                                 
                                 caption_dropout_rate: 0                        
                                 caption_dropout_every_n_epoc                   
                             hs: 0                                              
                                 caption_tag_dropout_rate:                      
                             0.0                                                
                                 caption_prefix: None                           
                                 caption_suffix: None                           
                                 color_aug: False                               
                                 flip_aug: False                                
                                 face_crop_aug_range: None                      
                                 random_crop: False                             
                                 token_warmup_min: 1,                           
                                 token_warmup_step: 0,                          
                                 alpha_mask: False                              
                                 resize_interpolation: None                     
                                 custom_attributes: {}                          
                                 is_reg: False                                  
                                 class_tokens: ohwx woman                       
                                 caption_extension: .txt                        
                                                                                
                                                                                
                    INFO     [Prepare dataset 0]              ]8;id=176456;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=268809;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#592\592]8;;\
                    INFO     loading image sizes.              ]8;id=281161;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=125141;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#987\987]8;;\
100%|███████████████████████████████████████| 10/10 [00:00<00:00, 476625.45it/s]
                    INFO     make buckets                     ]8;id=421694;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=925613;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1010\1010]8;;\
                    WARNING  min_bucket_reso and              ]8;id=767931;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=976583;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1027\1027]8;;\
                             max_bucket_reso are ignored if                     
                             bucket_no_upscale is set,                          
                             because bucket reso is defined                     
                             by image size automatically /                      
                             bucket_no_upscaleが指定された場                    
                             合は、bucketの解像度は画像サイズ                   
                             から自動計算されるため、min_buck                   
                             et_resoとmax_bucket_resoは無視さ                   
                             れます                                             
                    INFO     number of images (including      ]8;id=665640;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=479185;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1056\1056]8;;\
                             repeats) /                                         
                             各bucketの画像枚数（繰り返し回数                   
                             を含む）                                           
                    INFO     bucket 0: resolution (832,       ]8;id=906017;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=794337;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1061\1061]8;;\
                             1088), count: 10                                   
                    INFO     mean ar error (without repeats): ]8;id=805854;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=353557;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1069\1069]8;;\
                             0.014666190413822422                               
                    INFO     Checking the state dict: Diffusers ]8;id=717209;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=346236;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     prepare accelerator               ]8;id=331556;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=640561;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#186\186]8;;\
accelerator device: cuda
                    INFO     Building AutoEncoder              ]8;id=464197;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=907343;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#144\144]8;;\
                    INFO     Loading state dict from           ]8;id=575352;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=960489;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#149\149]8;;\
                             /kaggle/working/kohya_ss/ae.safet                  
                             ensors                                             
                    INFO     Loaded AE: <All keys matched      ]8;id=744754;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=864912;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#152\152]8;;\
                             successfully>                                      
2025-07-09 00:12:41 INFO     [Dataset 0]                      ]8;id=517553;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=868287;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2613\2613]8;;\
                    INFO     caching latents with caching     ]8;id=737822;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=912755;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1115\1115]8;;\
                             strategy.                                          
                    INFO     caching latents...               ]8;id=250206;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=842368;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1164\1164]8;;\
100%|█████████████████████████████████████████| 10/10 [00:00<00:00, 8700.07it/s]
/usr/local/lib/python3.12/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
  warnings.warn(
You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
2025-07-09 00:12:42 INFO     Building CLIP-L                   ]8;id=84353;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=335601;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#179\179]8;;\
                    INFO     Loading state dict from           ]8;id=316089;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=578045;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#275\275]8;;\
                             /kaggle/working/kohya_ss/clip_l.s                  
                             afetensors                                         
                    INFO     Loaded CLIP-L: <All keys matched  ]8;id=854030;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=967048;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#278\278]8;;\
                             successfully>                                      
                    INFO     Loading state dict from           ]8;id=616161;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=301630;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#330\330]8;;\
                             /kaggle/working/kohya_ss/t5xxl_fp                  
                             16.safetensors                                     
2025-07-09 00:12:47 INFO     Loaded T5xxl: <All keys matched   ]8;id=332447;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=603613;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#333\333]8;;\
                             successfully>                                      
2025-07-09 00:12:48 INFO     [Dataset 0]                      ]8;id=195800;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=34574;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2635\2635]8;;\
                    INFO     caching Text Encoder outputs     ]8;id=94187;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=711693;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1298\1298]8;;\
                             with caching strategy.                             
                    INFO     checking cache validity...       ]8;id=40518;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=883383;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1309\1309]8;;\
100%|█████████████████████████████████████████| 10/10 [00:00<00:00, 5098.84it/s]
                    INFO     no Text Encoder outputs to cache ]8;id=566860;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=716700;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1336\1336]8;;\
                    INFO     cache Text Encoder outputs for    ]8;id=547136;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=851054;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#249\249]8;;\
                             sample prompt:                                     
                             /kaggle/working/kohya_ss/training                  
                             _data/model/sample/prompt.txt                      
                    INFO     cache Text Encoder outputs for    ]8;id=618451;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=865351;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#259\259]8;;\
                             prompt: ohwx man close up                          
                             photoshoot                                         
                    INFO     cache Text Encoder outputs for    ]8;id=472449;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=516586;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#259\259]8;;\
                             prompt:                                            
2025-07-09 00:12:49 INFO     Checking the state dict: Diffusers ]8;id=831861;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=374727;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     Building Flux model dev from BFL  ]8;id=615592;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=660757;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#101\101]8;;\
                             checkpoint                                         
                    INFO     Loading state dict from           ]8;id=767022;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=284203;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#118\118]8;;\
                             /kaggle/working/kohya_ss/flux1-de                  
                             v.safetensors                                      
                    INFO     Loaded Flux: <All keys matched    ]8;id=178763;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=348689;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#137\137]8;;\
                             successfully>                                      
FLUX: Gradient checkpointing enabled. CPU offload: False
number of trainable parameters: 11901408320
prepare optimizer, data loader etc.
                    INFO     use Adafactor optimizer |        ]8;id=153467;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=896870;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4963\4963]8;;\
                             {'scale_parameter': False,                         
                             'relative_step': False,                            
                             'warmup_init': False,                              
                             'weight_decay': 0.01}                              
                    WARNING  because max_grad_norm is set,    ]8;id=665013;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=954220;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4991\4991]8;;\
                             clip_grad_norm is enabled.                         
                             consider set to 0 /                                
                             max_grad_normが設定されているた                    
                             めclip_grad_normが有効になります                   
                             。0に設定して無効にしたほうがい                    
                             いかもしれません                                   
                    WARNING  constant_with_warmup will be     ]8;id=27993;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=130488;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4995\4995]8;;\
                             good /                                             
                             スケジューラはconstant_with_warm                   
                             upが良いかもしれません                             
enable full bf16 training.
running training / 学習開始
  num examples / サンプル数: 10
  num batches per epoch / 1epochのバッチ数: 10
  num epochs / epoch数: 200
  batch size per device / バッチサイズ: 1
  gradient accumulation steps / 勾配を合計するステップ数 = 1
  total optimization steps / 学習ステップ数: 2000
steps:   0%|                                           | 0/2000 [00:00<?, ?it/s]
epoch 1/200
2025-07-09 00:12:53 INFO     epoch is incremented.             ]8;id=125509;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=410212;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 0, epoch: 1                         
steps:   0%|                  | 10/2000 [00:15<49:46,  1.50s/it, avr_loss=0.367]
epoch 2/200
2025-07-09 00:13:08 INFO     epoch is incremented.             ]8;id=557353;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=586435;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 1, epoch: 2                         
steps:   1%|▏                 | 20/2000 [00:29<49:15,  1.49s/it, avr_loss=0.349]
epoch 3/200
2025-07-09 00:13:23 INFO     epoch is incremented.             ]8;id=358226;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=537478;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 2, epoch: 3                         
steps:   2%|▎                 | 30/2000 [00:44<48:55,  1.49s/it, avr_loss=0.408]
epoch 4/200
2025-07-09 00:13:37 INFO     epoch is incremented.             ]8;id=109719;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=451103;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 3, epoch: 4                         
steps:   2%|▎                 | 40/2000 [00:59<48:38,  1.49s/it, avr_loss=0.406]
epoch 5/200
2025-07-09 00:13:52 INFO     epoch is incremented.             ]8;id=405246;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=791315;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 4, epoch: 5                         
steps:   2%|▍                 | 50/2000 [01:14<48:28,  1.49s/it, avr_loss=0.372]2025-07-09 00:14:07 INFO                                  ]8;id=196759;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=303953;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=716859;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=59308;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 50                                       
                    INFO     prompt: ohwx man close up   ]8;id=501215;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=936937;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=386293;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=852060;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=708610;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=598846;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=609181;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=710545;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=153028;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=548495;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx man close up photoshoot
Encoding prompt: ohwx man close up photoshoot

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steps:   2%|▍                 | 50/2000 [01:17<50:07,  1.54s/it, avr_loss=0.353]
epoch 6/200
2025-07-09 00:14:10 INFO     epoch is incremented.             ]8;id=24710;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=281763;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 5, epoch: 6                         
steps:   3%|▌                 | 60/2000 [01:32<49:35,  1.53s/it, avr_loss=0.413]
epoch 7/200
2025-07-09 00:14:25 INFO     epoch is incremented.             ]8;id=121251;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=124292;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 6, epoch: 7                         
steps:   4%|▋                 | 70/2000 [01:46<49:07,  1.53s/it, avr_loss=0.416]
epoch 8/200
2025-07-09 00:14:40 INFO     epoch is incremented.             ]8;id=935867;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=173548;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 7, epoch: 8                         
steps:   4%|▋                 | 80/2000 [02:01<48:41,  1.52s/it, avr_loss=0.387]
epoch 9/200
2025-07-09 00:14:54 INFO     epoch is incremented.             ]8;id=687339;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=864515;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 8, epoch: 9                         
steps:   4%|▊                 | 90/2000 [02:16<48:19,  1.52s/it, avr_loss=0.466]
epoch 10/200
2025-07-09 00:15:09 INFO     epoch is incremented.             ]8;id=492107;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=984391;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 9, epoch: 10                        
steps:   5%|▊                | 100/2000 [02:31<47:56,  1.51s/it, avr_loss=0.388]2025-07-09 00:15:24 INFO                                  ]8;id=443763;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=389550;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=668175;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=344665;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 100                                      
                    INFO     prompt: ohwx man close up   ]8;id=57989;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=163323;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=5825;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=180191;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=167790;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=798757;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=869884;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=593518;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=329116;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=566573;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx man close up photoshoot
Encoding prompt: ohwx man close up photoshoot

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steps:   5%|▊                | 100/2000 [02:33<48:40,  1.54s/it, avr_loss=0.373]
epoch 11/200
2025-07-09 00:15:26 INFO     epoch is incremented.             ]8;id=483388;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=132629;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 10, epoch: 11                       
steps:   6%|▉                | 110/2000 [02:48<48:15,  1.53s/it, avr_loss=0.429]
epoch 12/200
2025-07-09 00:15:41 INFO     epoch is incremented.             ]8;id=170670;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=398911;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 11, epoch: 12                       
steps:   6%|█                 | 120/2000 [03:03<47:51,  1.53s/it, avr_loss=0.38]
epoch 13/200
2025-07-09 00:15:56 INFO     epoch is incremented.             ]8;id=448783;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=576233;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 12, epoch: 13                       
steps:   6%|█                | 130/2000 [03:18<47:29,  1.52s/it, avr_loss=0.424]
epoch 14/200
2025-07-09 00:16:11 INFO     epoch is incremented.             ]8;id=498768;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=274318;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 13, epoch: 14                       
steps:   7%|█▏               | 140/2000 [03:32<47:09,  1.52s/it, avr_loss=0.351]
epoch 15/200
2025-07-09 00:16:26 INFO     epoch is incremented.             ]8;id=728614;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=296340;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 14, epoch: 15                       
steps:   8%|█▎               | 150/2000 [03:47<46:48,  1.52s/it, avr_loss=0.401]2025-07-09 00:16:40 INFO                                  ]8;id=179309;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=80755;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=205907;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=540259;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 150                                      
                    INFO     prompt: ohwx man close up   ]8;id=512595;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=256867;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=651642;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=57950;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=162969;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=356343;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=344501;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=683918;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=640886;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=781066;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx man close up photoshoot
Encoding prompt: ohwx man close up photoshoot

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steps:   8%|█▎               | 150/2000 [03:50<47:17,  1.53s/it, avr_loss=0.406]
epoch 16/200
2025-07-09 00:16:43 INFO     epoch is incremented.             ]8;id=121202;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=377614;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 15, epoch: 16                       
steps:   8%|█▎               | 160/2000 [04:04<46:55,  1.53s/it, avr_loss=0.362]
epoch 17/200
2025-07-09 00:16:58 INFO     epoch is incremented.             ]8;id=361841;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=949780;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 16, epoch: 17                       
steps:   8%|█▍               | 170/2000 [04:19<46:34,  1.53s/it, avr_loss=0.439]
epoch 18/200
2025-07-09 00:17:12 INFO     epoch is incremented.             ]8;id=226240;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=839721;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 17, epoch: 18                       
steps:   9%|█▌               | 180/2000 [04:34<46:14,  1.52s/it, avr_loss=0.469]
epoch 19/200
2025-07-09 00:17:27 INFO     epoch is incremented.             ]8;id=587115;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=723882;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 18, epoch: 19                       
steps:  10%|█▌               | 190/2000 [04:49<45:55,  1.52s/it, avr_loss=0.393]
epoch 20/200
2025-07-09 00:17:42 INFO     epoch is incremented.             ]8;id=769901;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=623430;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 19, epoch: 20                       
steps:  10%|█▋               | 200/2000 [05:03<45:35,  1.52s/it, avr_loss=0.434]2025-07-09 00:17:57 INFO                                  ]8;id=782333;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=300980;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=163367;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=787751;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 200                                      
                    INFO     prompt: ohwx man close up   ]8;id=582426;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=837457;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=362022;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=451573;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=761551;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=107821;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=112327;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=319589;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=906873;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=546295;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 21/200
2025-07-09 00:17:59 INFO     epoch is incremented.             ]8;id=576942;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=498934;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 20, epoch: 21                       
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epoch 22/200
2025-07-09 00:18:14 INFO     epoch is incremented.             ]8;id=223628;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=695464;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 21, epoch: 22                       
steps:  11%|█▊               | 220/2000 [05:35<45:17,  1.53s/it, avr_loss=0.413]
epoch 23/200
2025-07-09 00:18:29 INFO     epoch is incremented.             ]8;id=665041;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=48046;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 22, epoch: 23                       
steps:  12%|█▉               | 230/2000 [05:50<44:59,  1.52s/it, avr_loss=0.429]
epoch 24/200
2025-07-09 00:18:43 INFO     epoch is incremented.             ]8;id=422325;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=807047;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 23, epoch: 24                       
steps:  12%|██               | 240/2000 [06:05<44:40,  1.52s/it, avr_loss=0.362]
epoch 25/200
2025-07-09 00:18:58 INFO     epoch is incremented.             ]8;id=333137;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=639642;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 24, epoch: 25                       
steps:  12%|██▏              | 250/2000 [06:20<44:22,  1.52s/it, avr_loss=0.368]2025-07-09 00:19:13 INFO                                  ]8;id=131409;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=414297;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=225851;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=200966;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
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                             ステップ: 250                                      
                    INFO     prompt: ohwx man close up   ]8;id=110149;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=793481;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=638848;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=316482;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=536587;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=7096;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=580063;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=686481;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=19537;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=187114;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 26/200
2025-07-09 00:19:15 INFO     epoch is incremented.             ]8;id=684061;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=557525;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 25, epoch: 26                       
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epoch 27/200
2025-07-09 00:19:30 INFO     epoch is incremented.             ]8;id=756062;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=287681;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 26, epoch: 27                       
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epoch 28/200
2025-07-09 00:19:45 INFO     epoch is incremented.             ]8;id=476692;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=304275;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 27, epoch: 28                       
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epoch 29/200
2025-07-09 00:20:00 INFO     epoch is incremented.             ]8;id=320864;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=17091;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 28, epoch: 29                       
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epoch 30/200
2025-07-09 00:20:15 INFO     epoch is incremented.             ]8;id=412090;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=277840;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 29, epoch: 30                       
steps:  15%|██▌              | 300/2000 [07:36<43:08,  1.52s/it, avr_loss=0.375]2025-07-09 00:20:29 INFO                                  ]8;id=131629;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=620035;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=449608;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=635531;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
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                             ステップ: 300                                      
                    INFO     prompt: ohwx man close up   ]8;id=859209;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=304648;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=299320;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=209816;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=68856;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=806175;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=32455;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=195377;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=521247;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=337391;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 31/200
2025-07-09 00:20:32 INFO     epoch is incremented.             ]8;id=256227;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=279806;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 30, epoch: 31                       
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epoch 32/200
2025-07-09 00:20:46 INFO     epoch is incremented.             ]8;id=775657;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=757211;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 31, epoch: 32                       
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epoch 33/200
2025-07-09 00:21:01 INFO     epoch is incremented.             ]8;id=28024;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=469213;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 32, epoch: 33                       
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epoch 34/200
2025-07-09 00:21:16 INFO     epoch is incremented.             ]8;id=907750;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=514530;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 33, epoch: 34                       
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epoch 35/200
2025-07-09 00:21:31 INFO     epoch is incremented.             ]8;id=141915;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=843699;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 34, epoch: 35                       
steps:  18%|██▉              | 350/2000 [08:53<41:52,  1.52s/it, avr_loss=0.403]2025-07-09 00:21:46 INFO                                  ]8;id=529654;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=844561;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=650102;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=868533;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
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                             ステップ: 350                                      
                    INFO     prompt: ohwx man close up   ]8;id=275731;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=344934;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=462881;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=238575;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=816317;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=966078;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=746394;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=926804;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=882109;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=775264;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 36/200
2025-07-09 00:21:48 INFO     epoch is incremented.             ]8;id=48926;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=316647;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 35, epoch: 36                       
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epoch 37/200
2025-07-09 00:22:03 INFO     epoch is incremented.             ]8;id=276088;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=819035;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 36, epoch: 37                       
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epoch 38/200
2025-07-09 00:22:18 INFO     epoch is incremented.             ]8;id=220704;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=940046;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 37, epoch: 38                       
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epoch 39/200
2025-07-09 00:22:32 INFO     epoch is incremented.             ]8;id=726136;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=833085;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 38, epoch: 39                       
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epoch 40/200
2025-07-09 00:22:47 INFO     epoch is incremented.             ]8;id=97378;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=996083;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 39, epoch: 40                       
steps:  20%|███▍             | 400/2000 [10:09<40:37,  1.52s/it, avr_loss=0.455]2025-07-09 00:23:02 INFO                                  ]8;id=945756;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=559253;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=406886;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=63545;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 400                                      
                    INFO     prompt: ohwx man close up   ]8;id=338248;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=706567;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=893615;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=338000;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=174002;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=297426;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=807856;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=385552;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=425722;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=841478;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 41/200
2025-07-09 00:23:04 INFO     epoch is incremented.             ]8;id=749403;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=985589;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 40, epoch: 41                       
steps:  20%|███▉               | 410/2000 [10:26<40:29,  1.53s/it, avr_loss=0.4]
epoch 42/200
2025-07-09 00:23:19 INFO     epoch is incremented.             ]8;id=845846;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=624155;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 41, epoch: 42                       
steps:  21%|███▌             | 420/2000 [10:41<40:12,  1.53s/it, avr_loss=0.406]
epoch 43/200
2025-07-09 00:23:34 INFO     epoch is incremented.             ]8;id=837658;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=158969;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 42, epoch: 43                       
steps:  22%|███▋             | 430/2000 [10:56<39:55,  1.53s/it, avr_loss=0.324]
epoch 44/200
2025-07-09 00:23:49 INFO     epoch is incremented.             ]8;id=471767;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=823477;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 43, epoch: 44                       
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epoch 45/200
2025-07-09 00:24:04 INFO     epoch is incremented.             ]8;id=162384;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=399104;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 44, epoch: 45                       
steps:  22%|███▊             | 450/2000 [11:25<39:22,  1.52s/it, avr_loss=0.417]2025-07-09 00:24:18 INFO                                  ]8;id=62328;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=905811;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=56745;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=788755;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 450                                      
                    INFO     prompt: ohwx man close up   ]8;id=546176;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=792501;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=262971;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=565202;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=162024;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=213781;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=133037;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=826471;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=691619;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=788041;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 46/200
2025-07-09 00:24:21 INFO     epoch is incremented.             ]8;id=305617;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=553319;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 45, epoch: 46                       
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epoch 47/200
2025-07-09 00:24:36 INFO     epoch is incremented.             ]8;id=417736;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=568531;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 46, epoch: 47                       
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epoch 48/200
2025-07-09 00:24:50 INFO     epoch is incremented.             ]8;id=468045;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=667162;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 47, epoch: 48                       
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epoch 49/200
2025-07-09 00:25:05 INFO     epoch is incremented.             ]8;id=241543;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=940982;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 48, epoch: 49                       
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epoch 50/200
2025-07-09 00:25:20 INFO     epoch is incremented.             ]8;id=619157;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=365851;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 49, epoch: 50                       
steps:  25%|████▎            | 500/2000 [12:42<38:06,  1.52s/it, avr_loss=0.427]2025-07-09 00:25:35 INFO                                  ]8;id=230790;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=977936;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=12656;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=792119;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 500                                      
                    INFO     prompt: ohwx man close up   ]8;id=933412;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=883393;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=212682;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=162874;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=36157;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=315744;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=289251;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=645285;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=647425;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=164760;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 51/200
2025-07-09 00:25:37 INFO     epoch is incremented.             ]8;id=104569;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=568924;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 50, epoch: 51                       
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epoch 52/200
2025-07-09 00:25:52 INFO     epoch is incremented.             ]8;id=142952;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=794775;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 51, epoch: 52                       
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epoch 53/200
2025-07-09 00:26:07 INFO     epoch is incremented.             ]8;id=653846;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=866924;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 52, epoch: 53                       
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epoch 54/200
2025-07-09 00:26:22 INFO     epoch is incremented.             ]8;id=793572;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=643181;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 53, epoch: 54                       
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epoch 55/200
2025-07-09 00:26:36 INFO     epoch is incremented.             ]8;id=323445;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=259215;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 54, epoch: 55                       
steps:  28%|████▋            | 550/2000 [13:58<36:50,  1.52s/it, avr_loss=0.385]2025-07-09 00:26:51 INFO                                  ]8;id=510442;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=950192;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=911392;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=556543;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
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                             ステップ: 550                                      
                    INFO     prompt: ohwx man close up   ]8;id=522403;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=225412;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=225979;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=906039;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=610372;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=967949;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=868274;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=320298;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=507401;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=535494;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 56/200
2025-07-09 00:26:53 INFO     epoch is incremented.             ]8;id=573378;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=35693;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 55, epoch: 56                       
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epoch 57/200
2025-07-09 00:27:08 INFO     epoch is incremented.             ]8;id=813603;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=948358;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 56, epoch: 57                       
steps:  28%|█████▏            | 570/2000 [14:30<36:23,  1.53s/it, avr_loss=0.35]
epoch 58/200
2025-07-09 00:27:23 INFO     epoch is incremented.             ]8;id=444788;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=811248;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 57, epoch: 58                       
steps:  29%|████▉            | 580/2000 [14:45<36:07,  1.53s/it, avr_loss=0.351]
epoch 59/200
2025-07-09 00:27:38 INFO     epoch is incremented.             ]8;id=333455;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=599087;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 58, epoch: 59                       
steps:  30%|█████            | 590/2000 [14:59<35:50,  1.53s/it, avr_loss=0.343]
epoch 60/200
2025-07-09 00:27:53 INFO     epoch is incremented.             ]8;id=913335;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=673740;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 59, epoch: 60                       
steps:  30%|█████            | 600/2000 [15:14<35:34,  1.52s/it, avr_loss=0.341]2025-07-09 00:28:07 INFO                                  ]8;id=658570;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=709394;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=964368;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=638443;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 600                                      
                    INFO     prompt: ohwx man close up   ]8;id=757958;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=479040;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=950519;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=929537;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=483559;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=75973;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=408980;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=399707;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=973453;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=546149;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 61/200
2025-07-09 00:28:10 INFO     epoch is incremented.             ]8;id=912155;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=349780;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 60, epoch: 61                       
steps:  30%|█████▏           | 610/2000 [15:31<35:23,  1.53s/it, avr_loss=0.358]
epoch 62/200
2025-07-09 00:28:24 INFO     epoch is incremented.             ]8;id=321976;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=601868;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 61, epoch: 62                       
steps:  31%|█████▎           | 620/2000 [15:46<35:06,  1.53s/it, avr_loss=0.368]
epoch 63/200
2025-07-09 00:28:39 INFO     epoch is incremented.             ]8;id=362545;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=262908;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 62, epoch: 63                       
steps:  32%|█████▋            | 630/2000 [16:01<34:50,  1.53s/it, avr_loss=0.38]
epoch 64/200
2025-07-09 00:28:54 INFO     epoch is incremented.             ]8;id=225270;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=924611;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 63, epoch: 64                       
steps:  32%|█████▍           | 640/2000 [16:16<34:34,  1.53s/it, avr_loss=0.329]
epoch 65/200
2025-07-09 00:29:09 INFO     epoch is incremented.             ]8;id=504992;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=310496;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 64, epoch: 65                       
steps:  32%|█████▌           | 650/2000 [16:30<34:18,  1.52s/it, avr_loss=0.393]2025-07-09 00:29:24 INFO                                  ]8;id=486274;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=973410;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=291017;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=228696;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 650                                      
                    INFO     prompt: ohwx man close up   ]8;id=897628;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=581083;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=286236;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=905123;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=637676;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=620978;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=419245;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=331277;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=784223;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=288833;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 66/200
2025-07-09 00:29:26 INFO     epoch is incremented.             ]8;id=684756;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=813149;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 65, epoch: 66                       
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epoch 67/200
2025-07-09 00:29:41 INFO     epoch is incremented.             ]8;id=491090;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=264324;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 66, epoch: 67                       
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epoch 68/200
2025-07-09 00:29:56 INFO     epoch is incremented.             ]8;id=854392;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=77409;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 67, epoch: 68                       
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epoch 69/200
2025-07-09 00:30:10 INFO     epoch is incremented.             ]8;id=737099;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=625839;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 68, epoch: 69                       
steps:  34%|█████▊           | 690/2000 [17:32<33:18,  1.53s/it, avr_loss=0.383]
epoch 70/200
2025-07-09 00:30:25 INFO     epoch is incremented.             ]8;id=498995;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=126695;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 69, epoch: 70                       
steps:  35%|█████▉           | 700/2000 [17:47<33:02,  1.52s/it, avr_loss=0.411]2025-07-09 00:30:40 INFO                                  ]8;id=969165;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=892553;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=441201;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=376429;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 700                                      
                    INFO     prompt: ohwx man close up   ]8;id=548539;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=892599;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=814638;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=161086;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
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                    INFO     sample_steps: 20            ]8;id=946887;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=465587;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=562229;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=262027;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 71/200
2025-07-09 00:30:42 INFO     epoch is incremented.             ]8;id=989571;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=838270;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 70, epoch: 71                       
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epoch 72/200
2025-07-09 00:30:57 INFO     epoch is incremented.             ]8;id=154272;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=925225;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 71, epoch: 72                       
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epoch 73/200
2025-07-09 00:31:12 INFO     epoch is incremented.             ]8;id=456914;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=568787;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 72, epoch: 73                       
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epoch 74/200
2025-07-09 00:31:27 INFO     epoch is incremented.             ]8;id=594821;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=911666;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 73, epoch: 74                       
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epoch 75/200
2025-07-09 00:31:42 INFO     epoch is incremented.             ]8;id=399213;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=181247;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 74, epoch: 75                       
steps:  38%|██████▍          | 750/2000 [19:03<31:46,  1.53s/it, avr_loss=0.365]2025-07-09 00:31:57 INFO                                  ]8;id=912790;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=418142;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=463067;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=505763;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 750                                      
                    INFO     prompt: ohwx man close up   ]8;id=502480;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=860157;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=302308;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=124031;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=676388;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=373163;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=697876;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=95100;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=824189;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=818579;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
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epoch 76/200
2025-07-09 00:31:59 INFO     epoch is incremented.             ]8;id=208153;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=546769;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 75, epoch: 76                       
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epoch 77/200
2025-07-09 00:32:14 INFO     epoch is incremented.             ]8;id=466749;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=560928;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 76, epoch: 77                       
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epoch 78/200
2025-07-09 00:32:29 INFO     epoch is incremented.             ]8;id=114001;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=128645;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 77, epoch: 78                       
steps:  39%|██████▋          | 780/2000 [19:50<31:02,  1.53s/it, avr_loss=0.332]
epoch 79/200
2025-07-09 00:32:43 INFO     epoch is incremented.             ]8;id=810461;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=679995;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 78, epoch: 79                       
steps:  40%|██████▋          | 790/2000 [20:05<30:46,  1.53s/it, avr_loss=0.337]
epoch 80/200
2025-07-09 00:32:58 INFO     epoch is incremented.             ]8;id=203931;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=756550;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 79, epoch: 80                       
steps:  40%|██████▊          | 800/2000 [20:20<30:30,  1.53s/it, avr_loss=0.388]2025-07-09 00:33:13 INFO                                  ]8;id=508870;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=595621;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=883733;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=281629;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 800                                      
                    INFO     prompt: ohwx man close up   ]8;id=170996;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=164934;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=326487;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=169456;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=591266;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=565526;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=677978;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=472861;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=352967;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=573606;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx man close up photoshoot
Encoding prompt: ohwx man close up photoshoot

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epoch 81/200
2025-07-09 00:33:15 INFO     epoch is incremented.             ]8;id=447793;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=93159;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 80, epoch: 81                       
steps:  40%|██████▉          | 810/2000 [20:37<30:17,  1.53s/it, avr_loss=0.359]
epoch 82/200
2025-07-09 00:33:30 INFO     epoch is incremented.             ]8;id=990970;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=320112;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 81, epoch: 82                       
steps:  41%|██████▉          | 820/2000 [20:52<30:01,  1.53s/it, avr_loss=0.394]
epoch 83/200
2025-07-09 00:33:45 INFO     epoch is incremented.             ]8;id=323399;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=294696;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 82, epoch: 83                       
steps:  42%|███████          | 830/2000 [21:07<29:46,  1.53s/it, avr_loss=0.429]
epoch 84/200
2025-07-09 00:34:00 INFO     epoch is incremented.             ]8;id=393413;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=996387;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 83, epoch: 84                       
steps:  42%|███████▏         | 840/2000 [21:22<29:30,  1.53s/it, avr_loss=0.376]
epoch 85/200
2025-07-09 00:34:15 INFO     epoch is incremented.             ]8;id=759319;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=68386;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 84, epoch: 85                       
steps:  42%|███████▏         | 850/2000 [21:37<29:14,  1.53s/it, avr_loss=0.403]2025-07-09 00:34:30 INFO                                  ]8;id=847602;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=910376;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#59\59]8;;\
                    INFO     generating sample images at  ]8;id=341373;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=25052;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#60\60]8;;\
                             step / サンプル画像生成                            
                             ステップ: 850                                      
                    INFO     prompt: ohwx man close up   ]8;id=676677;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=621625;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#182\182]8;;\
                             photoshoot                                         
                    INFO     height: 512                 ]8;id=613456;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=323432;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#187\187]8;;\
                    INFO     width: 512                  ]8;id=663501;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=752390;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#188\188]8;;\
                    INFO     sample_steps: 20            ]8;id=802404;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=314789;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#189\189]8;;\
                    INFO     embedded guidance scale:    ]8;id=373386;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py\flux_train_utils.py]8;;\:]8;id=956498;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_train_utils.py#190\190]8;;\
                             3.5                                                
Using cached text encoder outputs for prompt: ohwx man close up photoshoot
Encoding prompt: ohwx man close up photoshoot

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epoch 86/200
2025-07-09 00:34:32 INFO     epoch is incremented.             ]8;id=857600;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=835014;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 85, epoch: 86                       
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epoch 87/200
2025-07-09 00:34:47 INFO     epoch is incremented.             ]8;id=921907;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=386628;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 86, epoch: 87                       
steps:  43%|███████▋          | 861/2000 [21:55<29:00,  1.53s/it, avr_loss=0.43]00:34:49-436976 INFO     The running process has been terminated.               
00:34:49-478261 INFO     Training has ended.                                    
00:35:15-775597 INFO     Copy                                                   
                         /kaggle/working/kohya_ss/dataset/sreeleela14/images to 
                         /kaggle/working/kohya_ss/training_data/img/1_ohwx      
                         man...                                                 
00:35:15-785307 INFO     Regularization images directory is missing... not      
                         copying regularisation images...                       
00:35:15-788127 INFO     Done creating kohya_ss training folder structure at    
                         /kaggle/working/kohya_ss/training_data...              
00:37:48-658089 INFO     Copy                                                   
                         /kaggle/working/kohya_ss/dataset/sreeleela14/images to 
                         /kaggle/working/kohya_ss/training_data/img/1_ohwx      
                         man...                                                 
00:37:48-667704 INFO     Regularization images directory is missing... not      
                         copying regularisation images...                       
00:37:48-670635 INFO     Done creating kohya_ss training folder structure at    
                         /kaggle/working/kohya_ss/training_data...              
00:38:41-098885 INFO     Start training Dreambooth...                           
00:38:41-101505 INFO     Validating lr scheduler arguments...                   
00:38:41-103720 INFO     Validating optimizer arguments...                      
00:38:41-105812 INFO     Validating /kaggle/working/kohya_ss/training_data/log  
                         existence and writability... SUCCESS                   
00:38:41-108139 INFO     Validating /kaggle/working/kohya_ss/training_data/model
                         existence and writability... SUCCESS                   
00:38:41-110449 INFO     Validating                                             
                         /kaggle/working/kohya_ss/flux1-dev.safetensors         
                         existence... SUCCESS                                   
00:38:41-112832 INFO     Validating /kaggle/working/kohya_ss/training_data/img  
                         existence... SUCCESS                                   
00:38:41-115818 INFO     Folder 1_ohwx man: 1 repeats found                     
00:38:41-118126 INFO     Folder 1_ohwx man: 15 images found                     
00:38:41-120206 INFO     Folder 1_ohwx man: 15 * 1 = 15 steps                   
00:38:41-122430 INFO     Regularization factor: 1                               
00:38:41-124376 INFO     Total steps: 15                                        
00:38:41-126794 INFO     Train batch size: 1                                    
00:38:41-129716 INFO     Gradient accumulation steps: 1                         
00:38:41-131806 INFO     Epoch: 200                                             
00:38:41-133794 INFO     max_train_steps (15 / 1 / 1 * 200 * 1) = 3000          
00:38:41-136233 INFO     lr_warmup_steps = 0                                    
00:38:41-139873 INFO     Saving training config to                              
                         /kaggle/working/kohya_ss/training_data/model/test_20250
                         709-003841.json...                                     
00:38:41-143795 INFO     Executing command: /usr/local/bin/accelerate launch    
                         --dynamo_backend no --dynamo_mode default              
                         --mixed_precision bf16 --num_processes 1 --num_machines
                         1 --num_cpu_threads_per_process 2                      
                         /kohya_ss/kohya_ss/sd-scripts/flux_train.py            
                         --config_file                                          
                         /kaggle/working/kohya_ss/training_data/model/config_dre
                         ambooth-20250709-003841.toml                           
ipex flag is deprecated, will be removed in Accelerate v1.10. From 2.7.0, PyTorch has all needed optimizations for Intel CPU and XPU.
2025-07-09 00:38:52 INFO     Loading settings from            ]8;id=146527;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=437168;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4651\4651]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/model/config_dreambooth-2                   
                             0250709-003841.toml...                             
2025-07-09 00:38:52 INFO     Using DreamBooth method.          ]8;id=311676;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=204194;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#115\115]8;;\
                    INFO     prepare images.                  ]8;id=768507;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=156842;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2072\2072]8;;\
                    INFO     get image size from name of      ]8;id=117236;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=608186;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1965\1965]8;;\
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                    INFO     set image size from cache files: ]8;id=644321;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=641625;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1995\1995]8;;\
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                    INFO     found directory                  ]8;id=377550;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=984415;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2019\2019]8;;\
                             /kaggle/working/kohya_ss/trainin                   
                             g_data/img/1_ohwx man contains                     
                             15 image files                                     
read caption: 100%|██████████████████████████| 15/15 [00:00<00:00, 91846.07it/s]
                    WARNING  No caption file found for 15     ]8;id=658064;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=846856;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2050\2050]8;;\
                             images. Training will continue                     
                             without captions for these                         
                             images. If class token exists,                     
                             it will be used. /                                 
                             15枚の画像にキャプションファイル                   
                             が見つかりませんでした。これらの                   
                             画像についてはキャプションなしで                   
                             学習を続行します。class                            
                             tokenが存在する場合はそれを使い                    
                             ます。                                             
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=545632;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=580521;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx man/Screenshot                   
                             from 2025-07-08 20-16-38.png                       
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=385046;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=311291;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx man/Screenshot                   
                             from 2025-07-08 20-16-45.png                       
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=883170;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=753102;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx man/Screenshot                   
                             from 2025-07-08 20-16-49.png                       
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=450295;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=421015;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx man/Screenshot                   
                             from 2025-07-08 20-16-54.png                       
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=249995;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=521154;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2057\2057]8;;\
                             g_data/img/1_ohwx man/Screenshot                   
                             from 2025-07-08 20-17-06.png                       
                    WARNING  /kaggle/working/kohya_ss/trainin ]8;id=858943;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=158066;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2055\2055]8;;\
                             g_data/img/1_ohwx man/Screenshot                   
                             from 2025-07-08 20-17-12.png...                    
                             and 10 more                                        
                    INFO     15 train images with repeats.    ]8;id=273307;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=437474;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2116\2116]8;;\
                    INFO     0 reg images with repeats.       ]8;id=115879;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=734596;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2120\2120]8;;\
                    WARNING  no regularization images /       ]8;id=944184;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=415393;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2125\2125]8;;\
                             正則化画像が見つかりませんでした                   
                    INFO     [Dataset 0]                      ]8;id=446416;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=159546;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#580\580]8;;\
                               batch_size: 1                                    
                               resolution: (1024, 1024)                         
                               resize_interpolation: None                       
                               enable_bucket: True                              
                               min_bucket_reso: 256                             
                               max_bucket_reso: 2048                            
                               bucket_reso_steps: 64                            
                               bucket_no_upscale: True                          
                                                                                
                               [Subset 0 of Dataset 0]                          
                                 image_dir:                                     
                             "/kaggle/working/kohya_ss/traini                   
                             ng_data/img/1_ohwx man"                            
                                 image_count: 15                                
                                 num_repeats: 1                                 
                                 shuffle_caption: False                         
                                 keep_tokens: 0                                 
                                 caption_dropout_rate: 0                        
                                 caption_dropout_every_n_epoc                   
                             hs: 0                                              
                                 caption_tag_dropout_rate:                      
                             0.0                                                
                                 caption_prefix: None                           
                                 caption_suffix: None                           
                                 color_aug: False                               
                                 flip_aug: False                                
                                 face_crop_aug_range: None                      
                                 random_crop: False                             
                                 token_warmup_min: 1,                           
                                 token_warmup_step: 0,                          
                                 alpha_mask: False                              
                                 resize_interpolation: None                     
                                 custom_attributes: {}                          
                                 is_reg: False                                  
                                 class_tokens: ohwx man                         
                                 caption_extension: .txt                        
                                                                                
                                                                                
                    INFO     [Prepare dataset 0]              ]8;id=802880;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py\config_util.py]8;;\:]8;id=684781;file:///kohya_ss/kohya_ss/sd-scripts/library/config_util.py#592\592]8;;\
                    INFO     loading image sizes.              ]8;id=155639;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=954254;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#987\987]8;;\
100%|████████████████████████████████████████| 15/15 [00:00<00:00, 59918.63it/s]
                    INFO     make buckets                     ]8;id=998890;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=474705;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1010\1010]8;;\
                    WARNING  min_bucket_reso and              ]8;id=701670;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=625807;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1027\1027]8;;\
                             max_bucket_reso are ignored if                     
                             bucket_no_upscale is set,                          
                             because bucket reso is defined                     
                             by image size automatically /                      
                             bucket_no_upscaleが指定された場                    
                             合は、bucketの解像度は画像サイズ                   
                             から自動計算されるため、min_buck                   
                             et_resoとmax_bucket_resoは無視さ                   
                             れます                                             
                    INFO     number of images (including      ]8;id=992287;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=916594;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1056\1056]8;;\
                             repeats) /                                         
                             各bucketの画像枚数（繰り返し回数                   
                             を含む）                                           
                    INFO     bucket 0: resolution (832, 832), ]8;id=498606;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=360023;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1061\1061]8;;\
                             count: 15                                          
                    INFO     mean ar error (without repeats): ]8;id=965984;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=243080;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1069\1069]8;;\
                             0.002270147559591429                               
                    INFO     Checking the state dict: Diffusers ]8;id=214410;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=579363;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     prepare accelerator               ]8;id=65304;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=844132;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#186\186]8;;\
accelerator device: cuda
                    INFO     Building AutoEncoder              ]8;id=754665;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=880899;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#144\144]8;;\
                    INFO     Loading state dict from           ]8;id=655638;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=1198;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#149\149]8;;\
                             /kaggle/working/kohya_ss/ae.safet                  
                             ensors                                             
                    INFO     Loaded AE: <All keys matched      ]8;id=255759;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=765752;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#152\152]8;;\
                             successfully>                                      
                    INFO     [Dataset 0]                      ]8;id=961564;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=595078;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2613\2613]8;;\
2025-07-09 00:38:53 INFO     caching latents with caching     ]8;id=569366;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=469730;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1115\1115]8;;\
                             strategy.                                          
                    INFO     caching latents...               ]8;id=978147;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=513054;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1164\1164]8;;\
100%|███████████████████████████████████████████| 15/15 [00:01<00:00, 14.72it/s]
/usr/local/lib/python3.12/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
  warnings.warn(
You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
2025-07-09 00:38:55 INFO     Building CLIP-L                   ]8;id=130873;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=574033;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#179\179]8;;\
                    INFO     Loading state dict from           ]8;id=838260;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=632485;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#275\275]8;;\
                             /kaggle/working/kohya_ss/clip_l.s                  
                             afetensors                                         
                    INFO     Loaded CLIP-L: <All keys matched  ]8;id=625252;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=836695;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#278\278]8;;\
                             successfully>                                      
                    INFO     Loading state dict from           ]8;id=192800;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=198591;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#330\330]8;;\
                             /kaggle/working/kohya_ss/t5xxl_fp                  
                             16.safetensors                                     
2025-07-09 00:39:00 INFO     Loaded T5xxl: <All keys matched   ]8;id=272688;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=499678;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#333\333]8;;\
                             successfully>                                      
2025-07-09 00:39:02 INFO     [Dataset 0]                      ]8;id=919360;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=156814;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#2635\2635]8;;\
                    INFO     caching Text Encoder outputs     ]8;id=733293;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=967922;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1298\1298]8;;\
                             with caching strategy.                             
                    INFO     checking cache validity...       ]8;id=739543;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=550055;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1309\1309]8;;\
100%|████████████████████████████████████████| 15/15 [00:00<00:00, 81390.12it/s]
                    INFO     caching Text Encoder outputs...  ]8;id=225654;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=938516;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#1340\1340]8;;\
100%|███████████████████████████████████████████| 15/15 [00:00<00:00, 21.49it/s]
                    INFO     cache Text Encoder outputs for    ]8;id=607854;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=288579;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#249\249]8;;\
                             sample prompt:                                     
                             /kaggle/working/kohya_ss/training                  
                             _data/model/sample/prompt.txt                      
                    INFO     cache Text Encoder outputs for    ]8;id=961482;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=831861;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#259\259]8;;\
                             prompt: ohwx man close up                          
                             photoshoot                                         
                    INFO     cache Text Encoder outputs for    ]8;id=120952;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py\flux_train.py]8;;\:]8;id=510073;file:///kohya_ss/kohya_ss/sd-scripts/flux_train.py#259\259]8;;\
                             prompt:                                            
                    INFO     Checking the state dict: Diffusers ]8;id=199626;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=254841;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#43\43]8;;\
                             or BFL, dev or schnell                             
                    INFO     Building Flux model dev from BFL  ]8;id=231169;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=390133;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#101\101]8;;\
                             checkpoint                                         
                    INFO     Loading state dict from           ]8;id=65213;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=105494;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#118\118]8;;\
                             /kaggle/working/kohya_ss/flux1-de                  
                             v.safetensors                                      
2025-07-09 00:39:03 INFO     Loaded Flux: <All keys matched    ]8;id=47431;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py\flux_utils.py]8;;\:]8;id=856812;file:///kohya_ss/kohya_ss/sd-scripts/library/flux_utils.py#137\137]8;;\
                             successfully>                                      
FLUX: Gradient checkpointing enabled. CPU offload: False
number of trainable parameters: 11901408320
prepare optimizer, data loader etc.
                    INFO     use Adafactor optimizer |        ]8;id=631421;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=713649;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4963\4963]8;;\
                             {'scale_parameter': False,                         
                             'relative_step': False,                            
                             'warmup_init': False,                              
                             'weight_decay': 0.01}                              
                    WARNING  because max_grad_norm is set,    ]8;id=635791;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=870408;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4991\4991]8;;\
                             clip_grad_norm is enabled.                         
                             consider set to 0 /                                
                             max_grad_normが設定されているた                    
                             めclip_grad_normが有効になります                   
                             。0に設定して無効にしたほうがい                    
                             いかもしれません                                   
                    WARNING  constant_with_warmup will be     ]8;id=874349;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=121683;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#4995\4995]8;;\
                             good /                                             
                             スケジューラはconstant_with_warm                   
                             upが良いかもしれません                             
enable full bf16 training.
running training / 学習開始
  num examples / サンプル数: 15
  num batches per epoch / 1epochのバッチ数: 15
  num epochs / epoch数: 200
  batch size per device / バッチサイズ: 1
  gradient accumulation steps / 勾配を合計するステップ数 = 1
  total optimization steps / 学習ステップ数: 3000
steps:   0%|                                           | 0/3000 [00:00<?, ?it/s]
epoch 1/200
2025-07-09 00:39:07 INFO     epoch is incremented.             ]8;id=752996;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=129913;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 0, epoch: 1                         
steps:   0%|                | 15/3000 [00:19<1:05:45,  1.32s/it, avr_loss=0.349]
epoch 2/200
2025-07-09 00:39:27 INFO     epoch is incremented.             ]8;id=710247;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py\train_util.py]8;;\:]8;id=730254;file:///kohya_ss/kohya_ss/sd-scripts/library/train_util.py#779\779]8;;\
                             current_epoch: 1, epoch: 2                         
steps:   1%|                | 18/3000 [00:23<1:05:23,  1.32s/it, avr_loss=0.357]