Shown here is the histogram of around 130K predictions of my deep neural network that is classifying some financial data. This is on the dev set but a similar distribution is also seen on the train set.
The output is a sigmoid function with a binary cross entropy loss. The output labels in the dataset are split 50:50 (1 or 0).
There is this large bar around 0.55 which is not mirrored by outputs that predict “negative”. Does that suggest something wrong with the network?
The performance of the network shows significant overfitting despite typical regularization techniques. The inputs are normalized using StandardScaler and I am not using batch normalization.