Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.007.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: 0.023356063291430473
Inter Cos: 0.09882697463035583
Norm Quadratic Average: 63.47124481201172
Nearest Class Center Accuracy: 0.35125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026774460449814796
Inter Cos: 0.09214501827955246
Norm Quadratic Average: 47.27130126953125
Nearest Class Center Accuracy: 0.376625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023468736559152603
Inter Cos: 0.06755512952804565
Norm Quadratic Average: 50.12190628051758
Nearest Class Center Accuracy: 0.408375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031151674687862396
Inter Cos: 0.08018417656421661
Norm Quadratic Average: 31.580190658569336
Nearest Class Center Accuracy: 0.435

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030471742153167725
Inter Cos: 0.07379943132400513
Norm Quadratic Average: 32.2796630859375
Nearest Class Center Accuracy: 0.48175

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04366292804479599
Inter Cos: 0.0812147855758667
Norm Quadratic Average: 20.33677864074707
Nearest Class Center Accuracy: 0.6045

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07761818915605545
Inter Cos: 0.08069171011447906
Norm Quadratic Average: 14.441243171691895
Nearest Class Center Accuracy: 0.93

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46038818359375
Linear Weight Rank: 4031
Intra Cos: 0.2645721137523651
Inter Cos: 0.11586929112672806
Norm Quadratic Average: 83.1297378540039
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.304912567138672
Linear Weight Rank: 3670
Intra Cos: 0.5767211318016052
Inter Cos: 0.22165338695049286
Norm Quadratic Average: 39.576942443847656
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.030177116394043
Linear Weight Rank: 10
Intra Cos: 0.7871302962303162
Inter Cos: 0.3017442226409912
Norm Quadratic Average: 25.827693939208984
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8887044191360474
Inter Cos: 0.3914380371570587
Norm Quadratic Average: 16.45530891418457
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.751479705810547
Accuracy: 0.5865
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20447814464569092, Weights: 0.017376171424984932
NC2 Equiangle: Features: 0.420969475640191, Weights: 0.09707397884792751
NC3 Self-Duality: 0.5384957790374756
NC4 NCC Mismatch: 0.14949999999999997

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: 0.022705599665641785
Inter Cos: 0.08705060184001923
Norm Quadratic Average: 63.184696197509766
Nearest Class Center Accuracy: 0.372

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026403279975056648
Inter Cos: 0.08141359686851501
Norm Quadratic Average: 47.03953552246094
Nearest Class Center Accuracy: 0.4

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022224636748433113
Inter Cos: 0.059958070516586304
Norm Quadratic Average: 49.948463439941406
Nearest Class Center Accuracy: 0.4425

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027620667591691017
Inter Cos: 0.07158049196004868
Norm Quadratic Average: 31.46185302734375
Nearest Class Center Accuracy: 0.4565

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026480840519070625
Inter Cos: 0.06585370004177094
Norm Quadratic Average: 32.176876068115234
Nearest Class Center Accuracy: 0.498

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03047006018459797
Inter Cos: 0.07199552655220032
Norm Quadratic Average: 20.21415901184082
Nearest Class Center Accuracy: 0.521

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03535396233201027
Inter Cos: 0.07447583973407745
Norm Quadratic Average: 14.284512519836426
Nearest Class Center Accuracy: 0.5995

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46038818359375
Linear Weight Rank: 4031
Intra Cos: 0.07508775591850281
Inter Cos: 0.13070876896381378
Norm Quadratic Average: 78.99024963378906
Nearest Class Center Accuracy: 0.611

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.304912567138672
Linear Weight Rank: 3670
Intra Cos: 0.1564028114080429
Inter Cos: 0.24386635422706604
Norm Quadratic Average: 35.40838623046875
Nearest Class Center Accuracy: 0.5855

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.030177116394043
Linear Weight Rank: 10
Intra Cos: 0.22147727012634277
Inter Cos: 0.3392428457736969
Norm Quadratic Average: 22.284189224243164
Nearest Class Center Accuracy: 0.5715

Output Layer:
Intra Cos: 0.27500391006469727
Inter Cos: 0.437400758266449
Norm Quadratic Average: 13.932260513305664
Nearest Class Center Accuracy: 0.5635

