Comments (2)
bmaltais
commented on July 28, 2024
2
I have been training some LoRA with 100 and another with 800 images. I have had some pretty good results.
For the 100 image dataset I usually use 50 repeats with TE LR of 5e-5 and UNet LR of 1e-3. I also enable flip and color augmentation. I also use WD14 captions with some tweaking and enable shuffle captions.
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LazyCat420
commented on July 28, 2024
If I want to get more epochs/checkpoints to save would it be better to increase batch size or increase epochs?
I'm guessing if I have the vram I could increase the batch size but then I have to increase the training rate by the same multiple.
If I increase epochs should I divide the repeats by the number of epochs?
Because with this version there's no steps so I'm kind of confused.
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Related Issues (20)
- Is it possible to train a LoRA model on a CPU? Has anyone successfully done this? HOT 2
- SD# Not seeing any samples HOT 2
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- any way to disable scheduled huber loss HOT 4
- does sdxl lora training train both text encoders or only 1? HOT 3
- Strange [Errno 13]. I think it's my fault. HOT 3
- Cache latents error HOT 1
- path with spaces error HOT 1
- How to train LORA with textEncoder 1 only. I get sdxl_train_network.py: error: unrecognized arguments: --train_text_encoder --learning_rate_te2=0" HOT 1
- I'm going to use the 4090 to fine-tune the large model of SDXL but I keep saying cuda is insufficient when I drive bisz to 1. HOT 2
- Multi GPU training not working HOT 2
- MultipleInvalid: extra keys not allowed @ data['datasets'][0]['subsets'][1]['is_reg']
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- dreambooth lora extraction = bad results.
- Full FP16 Dreambooth for SDXL does not work HOT 2
- Missing keys & size mismatch when merging LORAs
- Blue screen "video scheduler internal error" when using SD 3 branch with SD 3 training (normal branch XL works fine) HOT 1
- SD3 Gui Sampling + lora extraction HOT 1
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