may train with 0.0005 next time or somethin
may train with 0.0005 next time or somethin
IFor the sake of reporting, this was the error I was getting. Exception initializing accelerator: Accelerator.init() got an unexpected keyword argument 'project_dir'
IMaybe it can be useful. In my case after many hours online, I got easily distracted and didn't see that there are two files: requirements & requirements versions
IIf the training starts and finishes correctly, I will share my experience with you Dr Furkan.
IFirst update: In Dreambooth optimizer 8bit Adam is not there anymore. I have 1. Torch AdamW 2. Lion
Fyes this requires experimentation
Fyep this is version error
Fi spent like 5 hours first time i was trying to fix it 
IOK, the training started, so I can confirm that error above was my mistake.
INow with the exact same settings, as in your video, I'm getting this error:
IException training model: ''NoneType' object is not subscriptable'.
II will try to figure out what to change
Fcan you show entire message
IDo you want me to copy/paste message from terminal here? Or in private?
IIt's long.
IPlease check DM
Fyou can paste here
I Running training
Num batches each epoch = 0
Num Epochs = 200
Batch Size Per Device = 1
Gradient Accumulation steps = 1
Total train batch size (w. parallel, distributed & accumulation) = 1
Text Encoder Epochs: 150
Total optimization steps = 0
Total training steps = 0
Resuming from checkpoint: False
First resume epoch: 0
First resume step: 0
Lora: False, Optimizer: Torch AdamW, Prec: fp16
Gradient Checkpointing: False
EMA: True
UNET: True
Freeze CLIP Normalization Layers: False
LR: 1e-06
V2: False
Steps: : 0it [00:00, ?it/s]Traceback (most recent call last):
File "/workspace/stable-diffusion-webui/extensions/sd_dreambooth_extension/dreambooth/ui_functions.py", line 727, in start_training
result = main(class_gen_method=class_gen_method)
File "/workspace/stable-diffusion-webui/extensions/sd_dreambooth_extension/dreambooth/train_dreambooth.py", line 1448, in main
return inner_loop()
File "/workspace/stable-diffusion-webui/extensions/sd_dreambooth_extension/dreambooth/memory.py", line 119, in decorator
return function(batch_size, grad_size, prof, *args, **kwargs)
File "/workspace/stable-diffusion-webui/extensions/sd_dreambooth_extension/dreambooth/train_dreambooth.py", line 1200, in inner_loop
latents = batch["images"].to(accelerator.device)
TypeError: 'NoneType' object is not subscriptable
Steps: : 0it [00:00, ?it/s]
Restored system models.
Duration: 00:00:08
Num batches each epoch = 0
Num Epochs = 200
Batch Size Per Device = 1
Gradient Accumulation steps = 1
Total train batch size (w. parallel, distributed & accumulation) = 1
Text Encoder Epochs: 150
Total optimization steps = 0
Total training steps = 0
Resuming from checkpoint: False
First resume epoch: 0
First resume step: 0
Lora: False, Optimizer: Torch AdamW, Prec: fp16
Gradient Checkpointing: False
EMA: True
UNET: True
Freeze CLIP Normalization Layers: False
LR: 1e-06
V2: False
Steps: : 0it [00:00, ?it/s]Traceback (most recent call last):
File "/workspace/stable-diffusion-webui/extensions/sd_dreambooth_extension/dreambooth/ui_functions.py", line 727, in start_training
result = main(class_gen_method=class_gen_method)
File "/workspace/stable-diffusion-webui/extensions/sd_dreambooth_extension/dreambooth/train_dreambooth.py", line 1448, in main
return inner_loop()
File "/workspace/stable-diffusion-webui/extensions/sd_dreambooth_extension/dreambooth/memory.py", line 119, in decorator
return function(batch_size, grad_size, prof, *args, **kwargs)
File "/workspace/stable-diffusion-webui/extensions/sd_dreambooth_extension/dreambooth/train_dreambooth.py", line 1200, in inner_loop
latents = batch["images"].to(accelerator.device)
TypeError: 'NoneType' object is not subscriptable
Steps: : 0it [00:00, ?it/s]
Restored system models.
Duration: 00:00:08
Fdo pip reinstall -r requirements.txt again?
Falso you fixed versions right?
Fyou are using filewords?
IYes, versions fixed. Accelerate updated to 0.17 this morning was 0.16
F"I confirm, there is issue. I had the same error when some of "filewords" had the UTF16 LE encoding. With UTF8 it works properly."
FGitHub
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/sd_dreambooth_extension/scripts/dreambooth.py", line 455, in start_training result = main(config, use_txt2img=us...
II replicated your tutorial, just using my own token.
II will try the reinstall and update you
Fdo you use file captions? filewords?
Fi asked to extension developer
INo I don't think so. I'm only using images, renamed with a little description.
INow after the I reinstalled the requirements, I got a new error, so I can't launch web ui:
II gues the GPU is not avilable on Runpod, after I stopped it. GPUs have high availability, but my pod is set to 0 GPU.
IThank you!
II'm still waiting, lost GPU spot, now redoing everything again on a new pod.
IWill update you in a few minutes
Zwith the inspect emedding training program, do we have to check magnitude for overtraining or just strength?
B2.1 modeli çalıştırınca siyah box çıktısı alıyor sadece nasıl çözebilirim?
Fyou dont have to. best way is always comparing checkpoints
IOK, I reinstalled everything on a new machine, and I get the same erorr. But I'm not using filewords.
Fyour classification directory is invalid
Fput / beginning @I A
IYes I did..white space?
Fby the way you written them with incorrect order. above one is training below one is classification
Fyou noticed that right?
INO! Let me check...thanks
IOh yeah, it's working now. Your the man! Thanks
II will update you later.
Fyou are welcome
IMeanwhile I used some extra settings, based on your conclusions, like offset noise to 0.07, image genertion to DEISMultistep, and testing to deterministic.
Ztraining lower rate for longer seems to raise the magnitude which makes the embedding not play well with other prompts, so it seems like 0.005 is about as good as it's gonna get. Wonder if i make the backgrounds transparent if that will allow the ai to focus on the model better
ISo far so good, but gradio froze, so I cannot track the progress. I assume if I close the window, the training will stop? I can see it running on the terminal, tough.