Comments (1)
Hi, thanks for your interest in our work!
For pre-training on mini-ImageNet, on my end, it gets the highest validation accuracy (62.08 ± 0.20) at the end of the whole pre-training process, which is the 350 epoch.
Feel free to let me know if there's anything else I can help with.
from frn.
Related Issues (16)
- Are drop blocks used indeed? HOT 2
- Issue on the aux loss HOT 4
- Issue on pre-training HOT 10
- Performance on CUB HOT 2
- RuntimeError: inverse_cuda: For batch 0: U(2,2) is zero, singular U. HOT 3
- Validation accuracy of pre-training on the tieredImageNet dataset HOT 4
- pretrain accuracy HOT 12
- How to change the batch_size HOT 2
- About MatchingNet HOT 1
- How to predict new images with pre-trained model. HOT 4
- Issue on regularization HOT 3
- About the training process HOT 3
- Can authors open source the visualization part of the code? HOT 6
- Some data set links failed HOT 2
- Request for visualization code HOT 3
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from frn.