Firstly, I verified the predicted output value of the model.
1% of my data set (11 samples) as verification data.
The first time predicted output:
tensor([[ 2.3544, -1.6035], [-2.8536, 2.6495], [-1.4212, 0.3854], [-0.3363, -0.2809], [ 0.3346, -0.5889], [-1.1946, 2.2831], [-0.2375, -0.7653], [-0.1411, 0.0929], [-1.5674, 2.0254], [-0.0735, 0.0934], [ 1.3332, -1.3259]], device='cuda:0', grad_fn=<SqueezeBackward0>)
The second time predicted output:
tensor([[ 1.6338, -2.4857], [-2.7193, 2.8088], [-0.8641, 0.8308], [-0.6862, -0.8741], [-0.3699, -0.3573], [-1.7963, 1.0194], [ 0.2741, -0.1906], [-0.6578, -0.2878], [-1.3425, 2.3365], [ 0.1620, 0.3339], [ 0.8572, -1.2491]], device='cuda:0', grad_fn=<SqueezeBackward0>)
The third time predicted output:
tensor([[ 1.7435, -1.8670], [-2.4884, 2.8394], [-1.0321, 1.0768], [-0.5901, -0.0761], [ 0.0477, -0.6905], [-1.3724, 0.0560], [ 0.1470, -0.4054], [ 0.0067, 0.2553], [-1.7054, 1.6145], [ 0.3581, -0.2970], [ 1.3902, -1.1217]], device='cuda:0', grad_fn=<SqueezeBackward0>)
There are even minor changes! !
How could this be?