Thank you for your suggestions.
It was working. I just had a bug ion my code to calculate the validation accuracy. Here are the results (MSE Loss, Accuracy (assumption: if the output is within the 10% of the actual value, it is accurate)., and the learned weights from the final hidden layer to output layer i.e. 50 -> 1). I have followed your suggestions on decreasing the kernel size and increase the neurons in the fully connected layer. It seems like working.
Since, I am posting the results here, does the training/validation procedure look okay? Since I am comparing float values, which would not be 100% equal, I believe the fluctuations make sense, right?
Can you provide your view on the results?

CNN_who3372×2515 648 KB
 
CNNacc3288×2247 261 KB
 
CNNloss3255×2247 188 KB

also is the result to observe how the trained model behaves in a test set:

image1042×227 12.3 KB

Is there any way to improve this?
@ptrblck