Comments (2)
Ziyan-Huang
commented on June 18, 2024
In addition to the default nnU-Net settings, we have only adjusted the learning rate to be 10 times smaller. However, further tuning of the learning rate and the number of training epochs may potentially yield better results. Please follow the instructions in the README to reproduce the results, and feel free to experiment with these parameters. If you have any questions or need assistance, don't hesitate to ask.
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zhi-xuan-chen
commented on June 18, 2024
ok, thank you for your help！
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Related Issues (20)
- Label overlap HOT 2
- About the commands to pretraining the model HOT 4
- How to make the model run in DDP HOT 1
- about output channel and label HOT 2
- Can you provide the metrics evaluation scripts for the WORDS and FLARE datasets? HOT 4
- The unpacking dataset stopped for several hours
- Request for clarification on the architecture HOT 10
- huge model training supermemory problem HOT 3
- Direct evaluation HOT 4
- Are pretrained models compatible with nnUNet v2?
- Surpport 2D segmentation
- New label
- crop size is patch size?
- Some questions about the setting of initial_ir
- DP
- Issues about pkl files HOT 1
- Hello, I am truly sorry for interrupting your work HOT 5
- How to train from scratch(re-pretraining)? HOT 1
- How to use STUNet under nnUnet V2 version for completely starting from scratch training
- pickle error occurs when running the Direct Inference command
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