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gidariss / FeatureLearningRotNet

MIT License
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question about learning rate and rotate strategy #11

Closed CoinCheung closed 5 years ago

CoinCheung commented 5 years ago

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 5 years ago

Hi CoinCheung,

  1. Yes.
  2. No, it is not significantly worse. You might need to increase however the number of training epochs.
CoinCheung commented 5 years ago

Thanks for support !!