I have a model that predict four similar category numerical data (target values).
I use a CNN to extract feature for each category target value, before FC layers, I also add two values to the flattened extracted feature maps.
This works in Keras. I rewrite my codes with Pytorch. But the result of prediction for each category are almost same, with a little fluctuation.
I worry that this is caused by the back propagation.
The loss my model is RMSE of four target values of a training batch.
Any ideas?