0.117 s/epoch was time for 1000 samples of random dummy data, while my real data size is 51320 and 1.22 s/epoch corresponds to that.
My concern is with the comparison of CPU & GPU time for this real data of size 51320, in which i am not getting significant reduction in training time with GPU. (Also if i increase the size for random dummy data to 51320, times are almost the same)
For 14k model parameters: CPU: 5.7min GPU: 4.1min
I am not sure if i am doing everything i can, to get the maximum benefit from GPU.
Isn’t GPU benefit significant for model with only 14k parameters?