Average loss over epoch 1: 0.2288654596
Average loss over epoch 2: 0.1421572864
Average loss over epoch 3: 0.1162629128
Average loss over epoch 4: 0.1119744033
Average loss over epoch 5: 0.1090452522
Average loss over epoch 6: 0.1062508821
Average loss over epoch 7: 0.1051507816
Average loss over epoch 8: 0.1046195030
Average loss over epoch 9: 0.1010731906
Average loss over epoch 10: 0.0989995152
Average loss over epoch 11: 0.0968237147
Average loss over epoch 12: 0.0949065834
Average loss over epoch 13: 0.0951155946
Average loss over epoch 14: 0.0884226337
Average loss over epoch 15: 0.0864083916
Average loss over epoch 16: 0.0804556310
Average loss over epoch 17: 0.0763270557
Average loss over epoch 18: 0.0719402879
Average loss over epoch 19: 0.0686773658
Average loss over epoch 20: 0.0661188588
tensor([0.2955, 0.3533, 0.3168, 0.9707, 0.9785, 0.9007, 0.2950, 0.9873, 0.9873,
        0.3199, 0.2960, 0.9809, 0.9842, 0.2938, 0.9721, 0.9861, 0.3056, 0.9649,
        0.2938, 0.2953, 0.9699, 0.3481, 0.9758, 0.2950, 0.2965, 0.3004, 0.2938,
        0.2956, 0.9728, 0.9825, 0.4164, 0.3396, 0.3072, 0.2940, 0.9712, 0.6591,
        0.9840, 0.9843, 0.9831, 0.2939, 0.2938, 0.8865, 0.3151, 0.3238, 0.9626,
        0.9134, 0.3175, 0.3360, 0.9823, 0.2939, 0.8855, 0.9875, 0.4875, 0.9750,
        0.9257, 0.2942, 0.9840, 0.2968, 0.9875, 0.2959, 0.9870, 0.2963, 0.3162,
        0.3772, 0.3149, 0.9446, 0.3171, 0.9605, 0.2944, 0.9842, 0.3169, 0.9769,
        0.9804, 0.3164, 0.9358, 0.8684, 0.3207, 0.9842, 0.5466, 0.8285, 0.5587,
        0.2938, 0.3212, 0.9688, 0.9492, 0.2939, 0.9786, 0.3149, 0.9553, 0.2994,
        0.3278, 0.9836, 0.5737, 0.3153, 0.3890, 0.9244, 0.9739, 0.4678, 0.3195,
        0.9520, 0.5083, 0.3157, 0.9830, 0.9804, 0.7832, 0.9814, 0.4020, 0.2985,
        0.8494, 0.9791, 0.9851, 0.6223, 0.8703, 0.9609, 0.2947, 0.9665, 0.2970,
        0.3188, 0.9819, 0.3184, 0.3159, 0.7609, 0.9576, 0.9626, 0.3221, 0.3256,
        0.9772, 0.9776, 0.2937, 0.3154, 0.9865, 0.3227, 0.2952, 0.9563, 0.3179,
        0.9843, 0.5302, 0.6859, 0.3113, 0.9831, 0.9835, 0.9854, 0.9748, 0.3249,
        0.2937, 0.3151, 0.4493, 0.8058, 0.2946, 0.2938, 0.9866, 0.9823, 0.2943,
        0.4322, 0.3673, 0.3015, 0.9874, 0.9818, 0.3436, 0.2943, 0.9870, 0.9836,
        0.9859, 0.9792, 0.2977, 0.3091, 0.7377, 0.3205, 0.9008, 0.3028, 0.3245,
        0.2941, 0.3302, 0.3042, 0.9766, 0.9421, 0.9798, 0.3150, 0.9670, 0.9339,
        0.5895, 0.3139, 0.9736, 0.9808, 0.9683, 0.6304, 0.2973, 0.9140, 0.2940,
        0.2941, 0.9579, 0.8522, 0.3329, 0.9650, 0.2945, 0.7122, 0.3591, 0.2948,
        0.9845, 0.6018], grad_fn=<StackBackward0>)
Accuracy: 97.5%
Runtime: 2.06e+01 s or 3.43e-01 min.