I’ve been training ImageNet on resnet34_v1 on MXNet ~1.1.0, and I can get at best around 14% training accuracy after 1 epoch of training. However, with a different framework (BIDMach), I can get 29% training accuracy on the same. The command I am using to train is:
Easiest way is to run two epochs and you should get over 20% easily. Any reason why you are particularly interested in the accuracy after the first epoch?
You can also try some adaptive optimizers like adam to see if that works faster at initial stages.
I’m benchmarking MXNet against a different machine learning framework which is able to obtain 29% top-1 training accuracy after the first epoch. Clearly, achieving that kind of accuracy is possible. But I have not found a set of hyperparameters for MXNet which are able to achieve the same accuracy. Is there something else I could be doing wrong?