I chose to train a RNN for the task cos it has the capability to learn time series data better. Trained with different combinations of LSTM layers and output dimensions before converging to one combination. Then I tried CNN model for the same task.
What I found was CNN model could learn faster and gave about 65% accuracy at the end of 15 epochs, where as the RNN model took 50 epochs to get the same validation accuracy even after trying several learning rates. But at the end both models were giving about 65-70% validation accuracy after training for some more duration. I stopped my exploration there.
My question is I assumed/expected RNN to perform better. According to my understanding of RNN, it builds up the memory of time series data. What is it I am missing here ?