Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_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: 0.021450400352478027
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: 0.02554638497531414
Inter Cos: 0.11265513300895691
Norm Quadratic Average: 18.42576789855957
Nearest Class Center Accuracy: 0.31675

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027704861015081406
Inter Cos: 0.12216904014348984
Norm Quadratic Average: 10.793377876281738
Nearest Class Center Accuracy: 0.375125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04435970261693001
Inter Cos: 0.14554668962955475
Norm Quadratic Average: 10.626354217529297
Nearest Class Center Accuracy: 0.419

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08146118372678757
Inter Cos: 0.20387881994247437
Norm Quadratic Average: 6.753684043884277
Nearest Class Center Accuracy: 0.43425

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1415385603904724
Inter Cos: 0.2786661982536316
Norm Quadratic Average: 5.634297847747803
Nearest Class Center Accuracy: 0.450875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18168973922729492
Inter Cos: 0.35504624247550964
Norm Quadratic Average: 3.5246996879577637
Nearest Class Center Accuracy: 0.481

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2230200469493866
Inter Cos: 0.43331682682037354
Norm Quadratic Average: 2.533578634262085
Nearest Class Center Accuracy: 0.516125

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.8206787109375
Linear Weight Rank: 4031
Intra Cos: 0.2933024764060974
Inter Cos: 0.4680974781513214
Norm Quadratic Average: 12.106024742126465
Nearest Class Center Accuracy: 0.55775

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.780133247375488
Linear Weight Rank: 3670
Intra Cos: 0.3443291187286377
Inter Cos: 0.5483754873275757
Norm Quadratic Average: 9.240565299987793
Nearest Class Center Accuracy: 0.573

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.0496442317962646
Linear Weight Rank: 10
Intra Cos: 0.3818816840648651
Inter Cos: 0.6114920973777771
Norm Quadratic Average: 7.79961633682251
Nearest Class Center Accuracy: 0.567875

Output Layer:
Intra Cos: 0.4446491301059723
Inter Cos: 0.7044912576675415
Norm Quadratic Average: 7.285257816314697
Nearest Class Center Accuracy: 0.545375

Test Set:
Average Loss: 1.2147664413452148
Accuracy: 0.56
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2304048389196396, Weights: 0.12243109941482544
NC2 Equiangle: Features: 0.5806388007269965, Weights: 0.23301044040256078
NC3 Self-Duality: 0.33458980917930603
NC4 NCC Mismatch: 0.16100000000000003

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: 0.025505430996418
Inter Cos: 0.09568967670202255
Norm Quadratic Average: 18.2944393157959
Nearest Class Center Accuracy: 0.336

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029856080189347267
Inter Cos: 0.1054639145731926
Norm Quadratic Average: 10.700929641723633
Nearest Class Center Accuracy: 0.3935

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.044955309480428696
Inter Cos: 0.12796641886234283
Norm Quadratic Average: 10.54981517791748
Nearest Class Center Accuracy: 0.433

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07649626582860947
Inter Cos: 0.18106506764888763
Norm Quadratic Average: 6.712675094604492
Nearest Class Center Accuracy: 0.4485

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12152694165706635
Inter Cos: 0.24804195761680603
Norm Quadratic Average: 5.618992328643799
Nearest Class Center Accuracy: 0.463

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1421554684638977
Inter Cos: 0.3127773702144623
Norm Quadratic Average: 3.5178933143615723
Nearest Class Center Accuracy: 0.4735

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1782865673303604
Inter Cos: 0.37928739190101624
Norm Quadratic Average: 2.5291428565979004
Nearest Class Center Accuracy: 0.4915

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.8206787109375
Linear Weight Rank: 4031
Intra Cos: 0.24734961986541748
Inter Cos: 0.4816202223300934
Norm Quadratic Average: 12.096962928771973
Nearest Class Center Accuracy: 0.5395

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.780133247375488
Linear Weight Rank: 3670
Intra Cos: 0.3071998357772827
Inter Cos: 0.5621529221534729
Norm Quadratic Average: 9.251851081848145
Nearest Class Center Accuracy: 0.546

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.0496442317962646
Linear Weight Rank: 10
Intra Cos: 0.351211816072464
Inter Cos: 0.6250370144844055
Norm Quadratic Average: 7.82196569442749
Nearest Class Center Accuracy: 0.533

Output Layer:
Intra Cos: 0.4072722792625427
Inter Cos: 0.7172223925590515
Norm Quadratic Average: 7.32706356048584
Nearest Class Center Accuracy: 0.505

