Hi,
I had these stats calculated earlier.
For dataset A:
mean: [0.8279, 0.8259, 0.8216], std: [0.2331, 0.2331, 0.2458]
For dataset B:
mean: [0.4148, 0.3956, 0.3756], std: [0.2735, 0.2675, 0.2709]
So there does seem to be a large shift between the mean of the two datasets.
Naturally, the question now becomes: How could I modify the code to get good performance on dataset B? Or even better, on both datasets? I would have expected leaving batch norm in train() mode during evaluation to yield decent results (since it calculates the mean + std for each batch, rather than using running estimates), but that doesn’t seem to change anything either.
In the mean time, I’ll try the whole procedure again with the above stats. I’ll leave a reply after I’ve done that.