Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.03.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: 0.026582621037960052
Inter Cos: 0.10262076556682587
Norm Quadratic Average: 14.406402587890625
Nearest Class Center Accuracy: 0.314625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030444644391536713
Inter Cos: 0.1249721348285675
Norm Quadratic Average: 6.519768714904785
Nearest Class Center Accuracy: 0.381625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0587054081261158
Inter Cos: 0.19061966240406036
Norm Quadratic Average: 6.773057460784912
Nearest Class Center Accuracy: 0.397875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09657518565654755
Inter Cos: 0.29779699444770813
Norm Quadratic Average: 6.021449089050293
Nearest Class Center Accuracy: 0.3755

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.146284282207489
Inter Cos: 0.376675546169281
Norm Quadratic Average: 6.826742649078369
Nearest Class Center Accuracy: 0.37275

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.20359782874584198
Inter Cos: 0.44036582112312317
Norm Quadratic Average: 5.416301727294922
Nearest Class Center Accuracy: 0.375625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.245533749461174
Inter Cos: 0.4905155301094055
Norm Quadratic Average: 4.0228800773620605
Nearest Class Center Accuracy: 0.398875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.9989070892334
Linear Weight Rank: 4031
Intra Cos: 0.2619152367115021
Inter Cos: 0.5349874496459961
Norm Quadratic Average: 16.888181686401367
Nearest Class Center Accuracy: 0.42375

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.794438362121582
Linear Weight Rank: 3670
Intra Cos: 0.2786839008331299
Inter Cos: 0.5785796642303467
Norm Quadratic Average: 10.843897819519043
Nearest Class Center Accuracy: 0.431875

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.5961705446243286
Linear Weight Rank: 10
Intra Cos: 0.303154855966568
Inter Cos: 0.6208834052085876
Norm Quadratic Average: 7.458959102630615
Nearest Class Center Accuracy: 0.427625

Output Layer:
Intra Cos: 0.3457801938056946
Inter Cos: 0.6931868195533752
Norm Quadratic Average: 6.080954551696777
Nearest Class Center Accuracy: 0.410625

Test Set:
Average Loss: 1.4744160690307617
Accuracy: 0.434
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25690796971321106, Weights: 0.10090585052967072
NC2 Equiangle: Features: 0.7511769612630208, Weights: 0.280524656507704
NC3 Self-Duality: 0.39524751901626587
NC4 NCC Mismatch: 0.26749999999999996

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: 0.02837282232940197
Inter Cos: 0.08583037555217743
Norm Quadratic Average: 14.30486011505127
Nearest Class Center Accuracy: 0.334

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03295049071311951
Inter Cos: 0.10808622092008591
Norm Quadratic Average: 6.454013347625732
Nearest Class Center Accuracy: 0.3895

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05667834356427193
Inter Cos: 0.18242508172988892
Norm Quadratic Average: 6.707023620605469
Nearest Class Center Accuracy: 0.4015

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08488235622644424
Inter Cos: 0.28981220722198486
Norm Quadratic Average: 5.970566749572754
Nearest Class Center Accuracy: 0.386

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12816821038722992
Inter Cos: 0.3746839761734009
Norm Quadratic Average: 6.783520698547363
Nearest Class Center Accuracy: 0.3815

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1719440221786499
Inter Cos: 0.4431840777397156
Norm Quadratic Average: 5.389583110809326
Nearest Class Center Accuracy: 0.371

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.22491414844989777
Inter Cos: 0.49861106276512146
Norm Quadratic Average: 4.0082526206970215
Nearest Class Center Accuracy: 0.394

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.9989070892334
Linear Weight Rank: 4031
Intra Cos: 0.2636670172214508
Inter Cos: 0.5460927486419678
Norm Quadratic Average: 16.8604679107666
Nearest Class Center Accuracy: 0.4145

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.794438362121582
Linear Weight Rank: 3670
Intra Cos: 0.29319754242897034
Inter Cos: 0.5907989144325256
Norm Quadratic Average: 10.846663475036621
Nearest Class Center Accuracy: 0.4195

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.5961705446243286
Linear Weight Rank: 10
Intra Cos: 0.32492589950561523
Inter Cos: 0.6361657381057739
Norm Quadratic Average: 7.475517272949219
Nearest Class Center Accuracy: 0.4225

Output Layer:
Intra Cos: 0.382620245218277
Inter Cos: 0.7149461507797241
Norm Quadratic Average: 6.112487316131592
Nearest Class Center Accuracy: 0.4035

