gidariss/FeatureLearningRotNet

question about learning rate and rotate strategy

CoinCheung opened this issue · 2 comments

CoinCheung commented

Hi,

Thanks for providing this awesome work to us!!!

After reading the code, I am not sure whether I have fully understood it, so I feel I better open an issue to ask:

  1. the original cifar-10 is trained with learning-rate of 0.1 when the batchsize is 128. With the rotnet method, the batchsize is amplified to 512 (128x4) but the learning rate is still kept 0.1, is that right ?

  2. I see in the paper that the strategy of "simultaneously rotate the input image by 4 degrees and enlarge the batchsize 4 times" outperforms "randomly choose one degree to rotate and kept the batchsize not changed". Will the "randomly choose method" bring a significantly bad result, or it is only slightly outperformed by the proposed "4 rotates method" ?

I would be very happy to have your rely. Would you please show me your ideas on these details?

gidariss commented

Hi CoinCheung,

  1. Yes.
  2. No, it is not significantly worse. You might need to increase however the number of training epochs.
CoinCheung commented

Thanks for support !!