bier
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mop
CUB200 recall@1(0.575)
hi, i run your code using CUB200 dataset, but i can't reappear result of recall@1(0.575). Can you give me more detail about configure of parameters, likely training batch size, labels-per-batch? And how do you train, one stage or two stages? Thanks.
hi, i run your code using CUB200 dataset, but i can't reappear result of recall@1(0.575). Can you give me more detail about configure of parameters, likely training batch size, labels-per-batch? And how do you train, one stage or two stages? Thanks.
57.5% is ok
@kebinC did you solve the issue? What is the highest result you get?
No, the highest recall@1 i got is about 0.51.
@kebinC did you solve the issue? What is the highest result you get?
No, the highest recall@1 i got is about 0.51.
hi ,i only get 0.21@1 .How do you adjust the hyper parameter in the original code ?
hi, i run your code using CUB200 dataset, but i can't reappear result of recall@1(0.575). Can you give me more detail about configure of parameters, likely training batch size, labels-per-batch? And how do you train, one stage or two stages? Thanks.
57.5% is ok
By running the original repo , I only get 0.21@1 .Would you please give me some suggestion?Thank U.
@kebinC First, in line424 of train_bier.py, the axis should be 1, not 0. Have you implemented the baseline results? If you achieve similar baseline results, then you can try `activation', this will achieve R@1=~56.5.