Tensorboard: Should I be using the smoothed or normal value for evaluating accuracy?

Hi Everyone,

Pretty much in the title. I’m pretty sure that the smoothed
values are some sort of exponential moving average.

When evaluating the accuracy of the model (say, the accuracy I
want to tell people my model can achieve on the validation set, for
some nth epoch), should I be using the smoothed value or the normal
value? I take the accuracy every epoch.

Of course, this is before the ultimate test on the test set, but
before doing that, to kind of figure out what my max accuracy is,
and to gauge if the hyperparamaters i’m choosing are working,
should I be going by the smoothed or not smoothed values?

An example:

On step no. 151 (epoch 8)

smoothed accuracy (with smooth = 0.6) is 36.25%

“real” accuracy is 42.86%


Is my actual accuracy 36.25% or 42.86%? i



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