caffe loss NaN

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by Yangqing on 14 May 2014

For a sanity check, try running with a learning rate 0 to see if any nan errors pop up (they shouldn’t, since no learning takes place). If data is not initialized well, it might be possible that even 0.0001 is a too high learning rate.

by sguada on 13 May 2014

Try different initializations, for instance bias set to 0.1

References

  • On custom data training diverges (loss = NaN) #409
  • nan issue with CIFAR10 example when running on CPU only #393
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