For training and testing we use the data set of trajectories (10 ps long) propagated for the seven sites FMO complex from the Ref. Labels j for sites with initial excitation are 0 and 1 which respectively represent initial excitation on site-1 and site-6. We optimize 1D CNN architecture with the hyperopt library. Then, we train the 1D CNN using the Keras software package with the TensorFlow in the backend. The 1D CNN architecture that we used is given in Table with 0.001 as learning rate and 16 as batch size.