Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.001.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025611460208892822
Inter Cos: 0.10925440490245819
Norm Quadratic Average: 29.269268035888672
Nearest Class Center Accuracy: 0.318125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028288718312978745
Inter Cos: 0.11276346445083618
Norm Quadratic Average: 23.28167152404785
Nearest Class Center Accuracy: 0.3785

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036579765379428864
Inter Cos: 0.11697756499052048
Norm Quadratic Average: 28.07567024230957
Nearest Class Center Accuracy: 0.42075

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05626538395881653
Inter Cos: 0.1492086946964264
Norm Quadratic Average: 17.776872634887695
Nearest Class Center Accuracy: 0.447875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07056717574596405
Inter Cos: 0.1587946116924286
Norm Quadratic Average: 16.260944366455078
Nearest Class Center Accuracy: 0.477625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0924052819609642
Inter Cos: 0.1674438863992691
Norm Quadratic Average: 8.86087417602539
Nearest Class Center Accuracy: 0.52525

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12458174675703049
Inter Cos: 0.18254126608371735
Norm Quadratic Average: 6.514672756195068
Nearest Class Center Accuracy: 0.698625

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.6557388305664
Linear Weight Rank: 4031
Intra Cos: 0.3228939175605774
Inter Cos: 0.264396995306015
Norm Quadratic Average: 25.90153694152832
Nearest Class Center Accuracy: 0.972375

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.12343215942383
Linear Weight Rank: 3670
Intra Cos: 0.6030993461608887
Inter Cos: 0.4083377718925476
Norm Quadratic Average: 22.6976261138916
Nearest Class Center Accuracy: 0.998625

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.234604597091675
Linear Weight Rank: 10
Intra Cos: 0.7463053464889526
Inter Cos: 0.5123873949050903
Norm Quadratic Average: 26.804603576660156
Nearest Class Center Accuracy: 0.9995

Output Layer:
Intra Cos: 0.8099130392074585
Inter Cos: 0.6614301800727844
Norm Quadratic Average: 32.85600662231445
Nearest Class Center Accuracy: 0.996375

Test Set:
Average Loss: 2.873562713623047
Accuracy: 0.606
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25399988889694214, Weights: 0.04509760066866875
NC2 Equiangle: Features: 0.41483726501464846, Weights: 0.1635936525132921
NC3 Self-Duality: 0.43536490201950073
NC4 NCC Mismatch: 0.137

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352368116378784
Norm Quadratic Average: 27.530664443969727
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025239132344722748
Inter Cos: 0.09303569793701172
Norm Quadratic Average: 29.08618927001953
Nearest Class Center Accuracy: 0.3355

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029576556757092476
Inter Cos: 0.09836781024932861
Norm Quadratic Average: 23.138784408569336
Nearest Class Center Accuracy: 0.399

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03664863482117653
Inter Cos: 0.1031317412853241
Norm Quadratic Average: 27.959165573120117
Nearest Class Center Accuracy: 0.4505

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.052663564682006836
Inter Cos: 0.13162744045257568
Norm Quadratic Average: 17.701623916625977
Nearest Class Center Accuracy: 0.4635

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06329185515642166
Inter Cos: 0.1385766565799713
Norm Quadratic Average: 16.21302604675293
Nearest Class Center Accuracy: 0.482

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07598267495632172
Inter Cos: 0.14389804005622864
Norm Quadratic Average: 8.820609092712402
Nearest Class Center Accuracy: 0.4915

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08875662088394165
Inter Cos: 0.15329203009605408
Norm Quadratic Average: 6.457973003387451
Nearest Class Center Accuracy: 0.5355

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.6557388305664
Linear Weight Rank: 4031
Intra Cos: 0.1459721028804779
Inter Cos: 0.24463970959186554
Norm Quadratic Average: 24.981277465820312
Nearest Class Center Accuracy: 0.6095

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.12343215942383
Linear Weight Rank: 3670
Intra Cos: 0.21838770806789398
Inter Cos: 0.3673619329929352
Norm Quadratic Average: 21.27363395690918
Nearest Class Center Accuracy: 0.602

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.234604597091675
Linear Weight Rank: 10
Intra Cos: 0.24665352702140808
Inter Cos: 0.4537065029144287
Norm Quadratic Average: 24.887889862060547
Nearest Class Center Accuracy: 0.591

Output Layer:
Intra Cos: 0.2768595218658447
Inter Cos: 0.5655442476272583
Norm Quadratic Average: 30.353816986083984
Nearest Class Center Accuracy: 0.5715

