Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.02.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450398489832878
Inter Cos: 0.11371058225631714
Norm Quadratic Average: 27.691619873046875
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02478715591132641
Inter Cos: 0.09880369901657104
Norm Quadratic Average: 21.357118606567383
Nearest Class Center Accuracy: 0.302625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03070356324315071
Inter Cos: 0.11357961595058441
Norm Quadratic Average: 13.271669387817383
Nearest Class Center Accuracy: 0.358

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04457870498299599
Inter Cos: 0.1325545310974121
Norm Quadratic Average: 13.004549026489258
Nearest Class Center Accuracy: 0.409875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08035355806350708
Inter Cos: 0.18336418271064758
Norm Quadratic Average: 7.799803256988525
Nearest Class Center Accuracy: 0.432625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13150931894779205
Inter Cos: 0.25395578145980835
Norm Quadratic Average: 5.922056198120117
Nearest Class Center Accuracy: 0.456

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.16234925389289856
Inter Cos: 0.3489952087402344
Norm Quadratic Average: 3.3592689037323
Nearest Class Center Accuracy: 0.476625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2081499546766281
Inter Cos: 0.43949446082115173
Norm Quadratic Average: 2.339404821395874
Nearest Class Center Accuracy: 0.520125

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.82696533203125
Linear Weight Rank: 4031
Intra Cos: 0.2801625728607178
Inter Cos: 0.4806748330593109
Norm Quadratic Average: 11.385539054870605
Nearest Class Center Accuracy: 0.563125

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.785921096801758
Linear Weight Rank: 3670
Intra Cos: 0.3377290368080139
Inter Cos: 0.5420008897781372
Norm Quadratic Average: 8.924930572509766
Nearest Class Center Accuracy: 0.572

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.085991859436035
Linear Weight Rank: 10
Intra Cos: 0.38560551404953003
Inter Cos: 0.6155718564987183
Norm Quadratic Average: 7.714176177978516
Nearest Class Center Accuracy: 0.570875

Output Layer:
Intra Cos: 0.456748366355896
Inter Cos: 0.7108503580093384
Norm Quadratic Average: 7.410899639129639
Nearest Class Center Accuracy: 0.54925

Test Set:
Average Loss: 1.238089874267578
Accuracy: 0.5425
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23182740807533264, Weights: 0.12525977194309235
NC2 Equiangle: Features: 0.5750566694471572, Weights: 0.23578607771131727
NC3 Self-Duality: 0.3166232109069824
NC4 NCC Mismatch: 0.17300000000000004

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
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: 0.02595335990190506
Inter Cos: 0.08125897496938705
Norm Quadratic Average: 21.208419799804688
Nearest Class Center Accuracy: 0.3215

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03411554545164108
Inter Cos: 0.09635685384273529
Norm Quadratic Average: 13.17630672454834
Nearest Class Center Accuracy: 0.3645

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04709015414118767
Inter Cos: 0.11545199155807495
Norm Quadratic Average: 12.930849075317383
Nearest Class Center Accuracy: 0.425

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07772321999073029
Inter Cos: 0.16069389879703522
Norm Quadratic Average: 7.768790245056152
Nearest Class Center Accuracy: 0.444

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10586652159690857
Inter Cos: 0.22190560400485992
Norm Quadratic Average: 5.913303375244141
Nearest Class Center Accuracy: 0.4505

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12210778892040253
Inter Cos: 0.3020945191383362
Norm Quadratic Average: 3.3518102169036865
Nearest Class Center Accuracy: 0.4635

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.15911751985549927
Inter Cos: 0.3762513995170593
Norm Quadratic Average: 2.332157611846924
Nearest Class Center Accuracy: 0.4805

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.82696533203125
Linear Weight Rank: 4031
Intra Cos: 0.22804027795791626
Inter Cos: 0.4604352116584778
Norm Quadratic Average: 11.361916542053223
Nearest Class Center Accuracy: 0.5215

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.785921096801758
Linear Weight Rank: 3670
Intra Cos: 0.29129114747047424
Inter Cos: 0.5438228845596313
Norm Quadratic Average: 8.930286407470703
Nearest Class Center Accuracy: 0.529

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.085991859436035
Linear Weight Rank: 10
Intra Cos: 0.34318894147872925
Inter Cos: 0.6112238168716431
Norm Quadratic Average: 7.73382568359375
Nearest Class Center Accuracy: 0.521

Output Layer:
Intra Cos: 0.401228129863739
Inter Cos: 0.7012779712677002
Norm Quadratic Average: 7.454558849334717
Nearest Class Center Accuracy: 0.497

