Comments (4)
zzcqinag
commented on June 26, 2024
when you get 88.1% acc,did you train from finetune or just train from Scratch?
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abcdvzz
commented on June 26, 2024
when you get 88.1% acc,did you train from finetune or just train from Scratch?
finetune
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narrowsnap
commented on June 26, 2024
In my experiment, resnet50 got 88.23% accuracy, and resnet101 is worse than that.
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hyao1
commented on June 26, 2024
In my experiment, resnet50 got 88.23% accuracy, and resnet101 is worse than that.
are you modified something in source code except for dataset path. i only achieved 87.9% on cub
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Related Issues (20)
- RuntimeError: Error(s) in loading state_dict for DataParallel: HOT 4
- Fatal IO error: client killed HOT 5
- Why is your manual implementation via autograd.Function even faster than PyTorch 's autograd engine? HOT 2
- 1D version of Fast-MPN-Cov HOT 5
- Downloading problem? HOT 8
- CUB-200-20122数据集实验 HOT 2
- Should we use SVMs for FGVC? HOT 2
- fine tune issue HOT 4
- Loss and Accuracy dont change HOT 2
- what are suggested training parameters for CUB_200_2001? HOT 4
- can't download the pretrained pth HOT 1
- The performance of released model 'mpncovresnet50-15991845.pth' HOT 4
- the result of the combination of mpncov & efficientnet did not meet expectations
- About the implementation of MPNCOV meta layer in pytorch 0.3.1
- About the post-compensation implementation using trace
- Model parameters
- 模型参数下载 HOT 3
- gradcheck for Sqrtm in MPNCOV.py
- where should I put the pre-training model? HOT 1
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