Why the output is same within a batch use BertForSequenceClassification?
Author: 201101050424
Pull request: no
Labels: name: wontfix

## ❓ Questions & Help
I use BertForSequenceClassification for classification task, but the output witin a batch became same after just 2 or 3 batch, the value between different batch is different, really strange.
batch 1 output:
        [-0.5966,  0.6081],
        [-0.4659,  0.3766],
        [-0.3595,  0.1334],
        [-0.4178,  0.6873],
        [-0.3884,  0.2640],
        [-0.5017,  0.3465],
        [-0.5978,  0.4961],
        [-0.3146,  0.6879],
        [-0.6525,  0.2702],
        [-0.2500,  0.1232],
        [-0.3137,  0.4212],
        [-0.2663,  0.5169],
        [-0.5225,  0.7992],
        [-0.4844,  0.1942],
        [-0.1459,  0.4033],
        [-0.9007,  0.5122],
        [-0.5833,  0.8187],
        [-0.5552,  0.1253],
        [-0.5420, -0.1123]], device='cuda:0', grad_fn=<AddmmBackward>))
2:
(tensor(1.2256, device='cuda:0', grad_fn=<NllLossBackward>), tensor([[ 0.7105, -0.8978],
        [ 0.7925, -0.9382],
        [ 0.6098, -0.9100],
        [ 0.7522, -0.9534],
        [ 0.7706, -0.9142],
        [ 0.7778, -0.9246],
        [ 0.7703, -0.8327],
        [ 0.5850, -0.8817],
        [ 0.6266, -0.9271],
        [ 0.8061, -0.8157],
        [ 0.8036, -0.9927],
        [ 0.7619, -0.9277],
        [ 0.7773, -0.7931],
        [ 0.8458, -0.8186],
        [ 0.6291, -0.8925],
        [ 0.5919, -0.8709],
        [ 0.6222, -0.9173],
        [ 0.8290, -0.9817],
        [ 0.7155, -0.9171],
        [ 0.8107, -0.9364]], device='cuda:0', grad_fn=<AddmmBackward>))

3
(tensor(0.7688, device='cuda:0', grad_fn=<NllLossBackward>), tensor([[-0.7892,  0.5464],
        [-0.7873,  0.5431],
        [-0.7914,  0.5424],
        [-0.7938,  0.5448],
        [-0.7934,  0.5449],
        [-0.7876,  0.5430],
        [-0.7973,  0.5446],
        [-0.7905,  0.5430],
        [-0.7924,  0.5451],
        [-0.7900,  0.5438],
        [-0.7879,  0.5449],
        [-0.7869,  0.5408],
        [-0.7924,  0.5458],
        [-0.7928,  0.5436],
        [-0.7954,  0.5469],
        [-0.7900,  0.5429],
        [-0.7945,  0.5453],
        [-0.8027,  0.5492],
        [-0.7937,  0.5437],
        [-0.7934,  0.5506]], device='cuda:0', grad_fn=<AddmmBackward>))

(tensor(1.1733, device='cuda:0', grad_fn=<NllLossBackward>), tensor([[ 1.3647, -0.3074],
        [ 1.3588, -0.2927],
        [ 1.3581, -0.2915],
        [ 1.3628, -0.3009],
        [ 1.3625, -0.3001],
        [ 1.3630, -0.3016],
        [ 1.3666, -0.3157],
        [ 1.3604, -0.2953],
        [ 1.3655, -0.3108],
        [ 1.3604, -0.2942],
        [ 1.3623, -0.3041],
        [ 1.3555, -0.2866],
        [ 1.3600, -0.2943],
        [ 1.3654, -0.3091],
        [ 1.3628, -0.3004],
        [ 1.3658, -0.3080],
        [ 1.3643, -0.3041],
        [ 1.3599, -0.2967],
        [ 1.3629, -0.3024],
        [ 1.3688, -0.3206]], device='cuda:0', grad_fn=<AddmmBackward>))

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Comments:
Hello, could you provide a script so that we may better understand the problem here?

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