These are 10 inputs images and labels
tensor([[[[-0.0745, -0.0745, -0.0745,  ...,  0.3804,  0.3804,  0.3804],
          [-0.0667, -0.0667, -0.0667,  ...,  0.3804,  0.3804,  0.3804],
          [-0.0667, -0.0667, -0.0667,  ...,  0.3804,  0.3804,  0.3804],
          ...,
          [ 0.2392,  0.2235,  0.2157,  ..., -0.7020, -0.7020, -0.7020],
          [ 0.2235,  0.2000,  0.2314,  ..., -0.7020, -0.7098, -0.7020],
          [ 0.2235,  0.2235,  0.2706,  ..., -0.6941, -0.7020, -0.7176]]],


        [[[ 0.2784, -0.0745, -0.2863,  ..., -0.0196, -0.0667, -0.0824],
          [-0.0353, -0.2627, -0.0118,  ...,  0.0588,  0.0196,  0.0118],
          [-0.3098, -0.0902,  0.1922,  ...,  0.1294,  0.1059,  0.1059],
          ...,
          [-0.2706, -0.4039, -0.5922,  ..., -0.0275, -0.1608,  0.0902],
          [-0.4431, -0.3882, -0.5294,  ..., -0.0039, -0.1922,  0.0902],
          [-0.5216, -0.3176, -0.4275,  ...,  0.0353, -0.1216,  0.0902]]],


        [[[ 1.0000,  1.0000,  1.0000,  ...,  1.0000,  1.0000,  1.0000],
          [ 1.0000,  1.0000,  1.0000,  ...,  1.0000,  1.0000,  1.0000],
          [ 1.0000,  1.0000,  1.0000,  ...,  1.0000,  1.0000,  1.0000],
          ...,
          [-0.5059, -0.4980, -0.4667,  ..., -0.4667, -0.4510, -0.4588],
          [-0.5294, -0.5294, -0.5216,  ..., -0.4588, -0.4431, -0.4431],
          [-0.5294, -0.5137, -0.4902,  ..., -0.4824, -0.4980, -0.5059]]],


        ...,


        [[[-0.7961, -0.7961, -0.7961,  ..., -0.6627, -0.6549, -0.6549],
          [-0.7961, -0.7882, -0.7882,  ..., -0.6549, -0.6549, -0.6549],
          [-0.7882, -0.7882, -0.7882,  ..., -0.6471, -0.6549, -0.6549],
          ...,
          [-1.0000, -1.0000, -1.0000,  ..., -1.0000, -1.0000, -1.0000],
          [-1.0000, -0.9922, -1.0000,  ..., -0.9922, -1.0000, -1.0000],
          [-1.0000, -0.9922, -1.0000,  ..., -0.9922, -1.0000, -1.0000]]],


        [[[ 0.0902,  0.0353, -0.0039,  ...,  0.0980,  0.1137,  0.1059],
          [ 0.0902,  0.0588,  0.0275,  ...,  0.0745,  0.1059,  0.1137],
          [-0.0039,  0.0039, -0.0039,  ...,  0.0588,  0.0980,  0.0902],
          ...,
          [-0.6314, -0.6314, -0.6314,  ..., -0.5608, -0.5765, -0.5922],
          [-0.6392, -0.6314, -0.6157,  ..., -0.5843, -0.5922, -0.6078],
          [-0.6471, -0.6392, -0.6314,  ..., -0.5922, -0.5922, -0.5765]]],


        [[[-0.5765, -0.5765, -0.5765,  ..., -0.0902, -0.0980, -0.1059],
          [-0.5765, -0.5765, -0.5765,  ..., -0.0824, -0.0824, -0.0902],
          [-0.5843, -0.5843, -0.5843,  ..., -0.0667, -0.0667, -0.0667],
          ...,
          [-0.9686, -0.9686, -0.9686,  ..., -0.9451, -0.9373, -0.9294],
          [-0.9608, -0.9765, -0.9686,  ..., -0.9451, -0.9373, -0.9294],
          [-0.9608, -0.9765, -0.9765,  ..., -0.9451, -0.9451, -0.9294]]]],
       device='cuda:0')
tensor([0, 1, 0, 0, 0, 0, 1, 1, 0, 1], device='cuda:0')

And when I make the dataset small, I find that the loss begin to change from ≈0.80 to 0.69。
But still 0.69