No. of data sample: 1000
[epoch: 1] train loss: 36090.254560, val loss= 1.757510
[epoch: 2] train loss: 1387.862027, val loss= 0.520770
[epoch: 3] train loss: 3111.286146, val loss= 0.439036
[epoch: 4] train loss: 17.947500, val loss= 0.137422
[epoch: 5] train loss: 203.278646, val loss= 0.066220
[epoch: 6] train loss: 1334.001943, val loss= 3.633866
[epoch: 7] train loss: 1.166515, val loss= 1.024039
[epoch: 8] train loss: 1342.652672, val loss= 0.007894
[epoch: 9] train loss: 6.536866, val loss= 1.497171
[epoch: 10] train loss: 300.237195, val loss= 0.191258
[epoch: 11] train loss: 0.371061, val loss= 0.164196
[epoch: 12] train loss: 1.507313, val loss= 0.133595
[epoch: 13] train loss: 0.239755, val loss= 0.096481
[epoch: 14] train loss: 0.156767, val loss= 0.000084
No. of data sample :5000
[epoch: 1] train loss: 64015.036718, val loss= 39.728265
[epoch: 2] train loss: 4630.669958, val loss= 88.093311
[epoch: 3] train loss: 1109.897145, val loss= 0.530974
[epoch: 4] train loss: 0.429050, val loss= 0.000138
[epoch: 5] train loss: 0.001611, val loss= 0.000000
[epoch: 6] train loss: 0.000000, val loss= 0.000000
[epoch: 7] train loss: 0.000000, val loss= 0.000000
[epoch: 8] train loss: 0.000000, val loss= 0.000000
[epoch: 9] train loss: 0.000000, val loss= 0.000000
[epoch: 10] train loss: 0.000000, val loss= 0.000000
[epoch: 11] train loss: 0.000000, val loss= 0.000000
[epoch: 12] train loss: 0.000000, val loss= 0.000000
[epoch: 13] train loss: 0.000000, val loss= 0.000000
[epoch: 14] train loss: 0.000000, val loss= 0.000000
Sample input is img tensor, question tensor, ans tensor
MSE answer loss is being calculated