Oh Thanks, i have passed all those issue using the model i wrote in the previous comment.
Now i am adjusting my algorithm for the Reinforcement learning, but i wanted to be validate with you that i am doing something that make sense. Is this the right way to use 1D convolution for 12 channels (sensors) and 25 data points (time steps) ?
I am not asking about data cleaning, hyper parameters or model complexity, i am asking if this is the right shape of data to the 1d convolution problem as (batches, data points, channels) or (batches, channels, data points) fed to the forward function ?