So the predictions are very off but how can I fix them?
What should I change in my Network?
Here’s a snippet for step 1 in epoch 1:
size of train loader is:  90
predictions are:  tensor([[-0.0380, -0.1871,  0.0729, -0.3570, -0.2153,  0.3066,  1.1273, -0.0558],
        [-0.0316, -0.1876,  0.0317, -0.3613, -0.2333,  0.3023,  1.0940, -0.0665],
        [-0.0700, -0.1882,  0.0068, -0.3201, -0.1884,  0.2953,  1.0516, -0.0567],
        [-0.0844, -0.2009,  0.0573, -0.3166, -0.2597,  0.3127,  1.0343, -0.0573],
        [-0.0486, -0.2333,  0.0535, -0.3245, -0.2310,  0.2818,  1.0590, -0.0716],
        [-0.0240, -0.1989,  0.0572, -0.3135, -0.2435,  0.2912,  1.0612, -0.0560],
        [-0.0942, -0.2439,  0.0277, -0.3147, -0.2368,  0.2978,  1.0110, -0.0874],
        [-0.0356, -0.2285,  0.0064, -0.3179, -0.2432,  0.3083,  1.0300, -0.0756]],
       device='cuda:0', grad_fn=<AddmmBackward>)
landmarks are:  tensor([[501.9200, 240.1600, 691.0000, 358.0000, 295.0000, 294.0000, 488.6482,
         279.6466],
        [495.6300, 246.0600, 692.0000, 235.0000, 286.0000, 242.0000, 464.0000,
         339.0000],
        [488.7100, 240.8900, 613.4007, 218.3425, 281.0000, 220.0000, 415.9966,
         338.4796],
        [502.5721, 245.4983, 640.0000, 131.0000, 360.0000, 143.0000, 542.9840,
         321.8463],
        [505.1393, 246.4364, 700.0000, 306.0000, 303.0000, 294.0000, 569.6925,
         351.8367],
        [501.0900, 244.0100, 724.0000, 251.0000, 302.0000, 276.0000, 504.6415,
         291.7443],
        [495.9500, 244.2800, 608.0000, 127.0000, 323.0000, 166.0000, 491.0000,
         333.0000],
        [490.2500, 241.3400, 699.0000, 304.0000, 398.6197, 313.8339, 429.1374,
         303.8483]], device='cuda:0')
loss_train_step before backward:  tensor(166475.6875, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train_step after backward:  tensor(166475.6875, device='cuda:0', grad_fn=<MseLossBackward>)
loss_train:  166475.6875
step:  1
running loss:  166475.6875
Train Steps: 1/90  Loss: 166475.6875

Here’s the full log: https://pastebin.com/raw/Jt98BvTx 2