Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.0007.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: 0.023754633963108063
Inter Cos: 0.07931233197450638
Norm Quadratic Average: 85.6964340209961
Nearest Class Center Accuracy: 0.345

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02995092049241066
Inter Cos: 0.08240410685539246
Norm Quadratic Average: 64.24638366699219
Nearest Class Center Accuracy: 0.37525

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026055825874209404
Inter Cos: 0.06546143442392349
Norm Quadratic Average: 67.30951690673828
Nearest Class Center Accuracy: 0.405375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03569230064749718
Inter Cos: 0.08234091848134995
Norm Quadratic Average: 43.45513916015625
Nearest Class Center Accuracy: 0.42625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03406821936368942
Inter Cos: 0.06608181446790695
Norm Quadratic Average: 44.21345520019531
Nearest Class Center Accuracy: 0.459375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.047540485858917236
Inter Cos: 0.08305332064628601
Norm Quadratic Average: 28.22119903564453
Nearest Class Center Accuracy: 0.543625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06352495402097702
Inter Cos: 0.07520312815904617
Norm Quadratic Average: 19.920469284057617
Nearest Class Center Accuracy: 0.831875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.046142578125
Linear Weight Rank: 4031
Intra Cos: 0.1815599799156189
Inter Cos: 0.10222216695547104
Norm Quadratic Average: 106.19342803955078
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.63536834716797
Linear Weight Rank: 3671
Intra Cos: 0.40540608763694763
Inter Cos: 0.1955804079771042
Norm Quadratic Average: 54.79680633544922
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4676389694213867
Linear Weight Rank: 10
Intra Cos: 0.6304260492324829
Inter Cos: 0.29502296447753906
Norm Quadratic Average: 37.95858383178711
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8644738793373108
Inter Cos: 0.49822279810905457
Norm Quadratic Average: 25.72266387939453
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.5328555297851563
Accuracy: 0.6025
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21285855770111084, Weights: 0.020469676703214645
NC2 Equiangle: Features: 0.4386662801106771, Weights: 0.08448505931430393
NC3 Self-Duality: 0.6326884031295776
NC4 NCC Mismatch: 0.14100000000000001

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: 0.02343386970460415
Inter Cos: 0.07222629338502884
Norm Quadratic Average: 85.49060821533203
Nearest Class Center Accuracy: 0.3595

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029713181778788567
Inter Cos: 0.07877479493618011
Norm Quadratic Average: 64.06590270996094
Nearest Class Center Accuracy: 0.407

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025443285703659058
Inter Cos: 0.05973737686872482
Norm Quadratic Average: 67.18019104003906
Nearest Class Center Accuracy: 0.4365

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03307560831308365
Inter Cos: 0.0818747952580452
Norm Quadratic Average: 43.327537536621094
Nearest Class Center Accuracy: 0.4415

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030054988339543343
Inter Cos: 0.06533858180046082
Norm Quadratic Average: 44.048187255859375
Nearest Class Center Accuracy: 0.47

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03547755256295204
Inter Cos: 0.07836761325597763
Norm Quadratic Average: 28.05792808532715
Nearest Class Center Accuracy: 0.4915

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036289412528276443
Inter Cos: 0.06931386888027191
Norm Quadratic Average: 19.716476440429688
Nearest Class Center Accuracy: 0.5605

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.046142578125
Linear Weight Rank: 4031
Intra Cos: 0.06086092069745064
Inter Cos: 0.10025116056203842
Norm Quadratic Average: 102.33240509033203
Nearest Class Center Accuracy: 0.6115

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.63536834716797
Linear Weight Rank: 3671
Intra Cos: 0.11879416555166245
Inter Cos: 0.19366265833377838
Norm Quadratic Average: 50.636756896972656
Nearest Class Center Accuracy: 0.602

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4676389694213867
Linear Weight Rank: 10
Intra Cos: 0.18140055239200592
Inter Cos: 0.30586808919906616
Norm Quadratic Average: 33.82554244995117
Nearest Class Center Accuracy: 0.5875

Output Layer:
Intra Cos: 0.2629304826259613
Inter Cos: 0.47786659002304077
Norm Quadratic Average: 22.277307510375977
Nearest Class Center Accuracy: 0.5755

