I have an simple dataset where the input is 55 floating point features and each sample has a classification output as 0 or 1. The dataset is split roughly equally in terms of how many samples of each class there are.
I can get good performance during training, but when using eval() my model will only output zeros.
The model is as follows:
model = nn.Sequential(
I have tried setting track_running_stats to False for the bn layers, and when using eval() the model outputs actual values, but they are all roughly between 0.2 & 0.3 so the classification as 0 or 1 is still poor.
Is there something I am fundamentally misunderstanding? I should add that my batch size is 128.