print(final_inputs,final_inputs.isnan().any())
tensor([[ 4.5512e+03,  2.2965e+03,  3.7338e+03, -1.1410e+03],
        [-1.2685e+04,  2.1673e+05,  2.7743e+05,  2.2019e+05],
        [ 1.3482e+03,  4.0191e+04,  1.5236e+04,  8.1835e+03],
        ...,
        [ 4.0465e+04,  2.3288e+04,  2.5682e+04,  6.2736e+03],
        [ 7.3675e+05, -9.9548e+05, -1.4421e+06,  1.7742e+04],
        [ 1.3802e+03,  9.2324e+02,  9.4439e+02,  3.3211e+01]],
       grad_fn=<AddmmBackward>) tensor(False)
Epoch 0, Iteration: 0.000, Loss:72828.328
tensor([[ 4.8688e+17, -5.5222e+16,  2.8847e+17, -7.2008e+17],
        [ 4.8875e+17, -5.5577e+16,  2.8895e+17, -7.2208e+17],
        [ 2.8952e+19, -3.2968e+18,  1.7122e+19, -4.2774e+19],
        ...,
        [ 2.7599e+15, -3.1438e+14,  1.6323e+15, -4.0776e+15],
        [ 6.9775e+18, -7.9428e+17,  4.1225e+18, -1.0305e+19],
        [ 2.7847e+19, -3.1713e+18,  1.6469e+19, -4.1142e+19]],
       grad_fn=<AddmmBackward>) tensor(False)
Epoch 0, Iteration: 1.000, Loss:479207024681287680.000
tensor([[-7.4644e+29,  9.6666e+25,  7.4367e+29,  2.6739e+27],
        [-2.0749e+33,  2.6870e+29,  2.0672e+33,  7.4327e+30],
        [-1.8951e+30,  2.4542e+26,  1.8880e+30,  6.7886e+27],
        ...,
        [-1.2698e+30,  1.6444e+26,  1.2650e+30,  4.5486e+27],
        [-1.7603e+33,  2.2796e+29,  1.7537e+33,  6.3057e+30],
        [-2.1945e+30,  2.8420e+26,  2.1864e+30,  7.8614e+27]],
       grad_fn=<AddmmBackward>) tensor(False)
Epoch 0, Iteration: 2.000, Loss:301857268183970173654388944404480.000
tensor([[ 1.2171e+14,  2.3199e+10, -1.2212e+14,  3.9526e+11],
        [ 1.2171e+14,  2.3199e+10, -1.2212e+14,  3.9526e+11],
        [ 1.2171e+14,  2.3199e+10, -1.2212e+14,  3.9526e+11],
        ...,
        [ 1.2171e+14,  2.3199e+10, -1.2212e+14,  3.9526e+11],
        [ 1.2171e+14,  2.3199e+10, -1.2212e+14,  3.9526e+11],
        [ 1.2171e+14,  2.3199e+10, -1.2212e+14,  3.9526e+11]],
       grad_fn=<AddmmBackward>) tensor(False)
Epoch 0, Iteration: 3.000, Loss:67027314147328.000
tensor([[-8.5834e+19,  1.3941e+16,  8.5509e+19,  3.1127e+17],
        [-8.5834e+19,  1.3941e+16,  8.5509e+19,  3.1127e+17],
        [-8.5834e+19,  1.3941e+16,  8.5509e+19,  3.1127e+17],
        ...,
        [-8.5834e+19,  1.3941e+16,  8.5509e+19,  3.1127e+17],
        [-8.5834e+19,  1.3941e+16,  8.5509e+19,  3.1127e+17],
        [-8.5834e+19,  1.3941e+16,  8.5509e+19,  3.1127e+17]],
       grad_fn=<AddmmBackward>) tensor(False)

After this point, I get this -RuntimeError: Function ‘LogSoftmaxBackward’ returned nan values in its 0th output.