One problem came when I was using SwinUNETR to train my own data about research-contributions HOT 5 OPEN

@tangy5 Hi!

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Hi @wangbaoyuanGUET ,great to see you are training your own data. looks like the model checkpoint is not good enough, not related to Swin-UNETR parameter
, or maybe there are errors in the pre-processing steps.
you could check:

1. whether the image is padded to 64x64x64. (Add spatial pad transform)
2. monitor the validation metrics to see if the model training is converged. transformer models are typically harder to converge.
3. Whether loss functions are properly set with 2 classes.
4. Input/output channels is correct.
5. When doing inference, whether the model checkpoint is loaded.

Following your successful prediction, you could check if everything else is the same except the backbone.

Hope above helps and let me know if you have more details or findings.

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@tangy5
Thanks for your reply very very much！
I contact deep learning from few months ago, although I don't have a good foundation, I kept working on my coding skills.
So I was pleasantly surprised to hear from you so quickly.
I will check my code according to your valuable opinions.
Thank you again!

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Hi! Mr.Tangy @tangy5
I'm glad to tell you about that I've solved the problem I mentioned before.
I guessd that the problem is caused by the roi_size of (64, 64, 64).
When the preprocessing method called RandCropByPosNegLabeld crops the data into 4 patches, the roi_size (64, 64, 64) may not cover the entire image. When testing, so does it.
So I change the roi_size to (96, 96, 32) and the problem stopped coming up.
Right now I'm running a new personal dataset to test the validity of my own models.
I appreciate for your help which is important to me.
By the way, the Monai framework is very very great and I like it !

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