Comments (2)
Thanks for the information.
from bk-sdm.
Hi, thanks for your inquiry.
For our text-to-image experiments, we simply set the loss weights λ_Task, λ_OutKD, and λ_FeatKD to 1, which was effective in empirical validation without hyperparameter tuning and was used in the experiments of our paper.
In recent trials with BK-SDM-Small and batch size 64, changing λ_FeatKD to {0.25, 0.5, 1, 2, 4} did not affect the final generation scores. However, using different scales like 0.01, 0.1, 10, or 100 hasn't been explored.
It would be interesting to study the effect of different loss weightings.
added: some experimental results were as follows:
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recent trials with BK-SDM-Small, batch size 64, changing λ_FeatKD to {0.25, 0.5, 1, 2, 4}
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the ablation study presented in our paper (v: loss weight = 1, x: loss weight = 0)
from bk-sdm.
Related Issues (20)
- Add downloading 2.3M LAION training pairs
- Refine generation code
- SDXL support? HOT 1
- Add DreamBooth finetuning
- Scale of KD-feature loss for SD inpainting 1.5 HOT 11
- Snapfusion seems to get better results? HOT 3
- data loading problem with 89M pairs HOT 9
- Discussion on preprocessing of LAION data HOT 3
- Discussion on experimental settings HOT 7
- Question of Dreambooth evaluation HOT 6
- improved wandb logger
- batched image generation
- Is there someway to test Img2Img? HOT 1
- any plans for more models? HOT 1
- About the training speed HOT 3
- About gpu memory HOT 2
- how about kd trianing without ema? HOT 1
- May I ask if the training time is not accurate HOT 1
- issue about training iterations HOT 1
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