Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.001.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: 0.024517877027392387
Inter Cos: 0.09569849073886871
Norm Quadratic Average: 32.765506744384766
Nearest Class Center Accuracy: 0.303125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03146215155720711
Inter Cos: 0.10189773887395859
Norm Quadratic Average: 25.61359977722168
Nearest Class Center Accuracy: 0.368875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0357908271253109
Inter Cos: 0.0991031751036644
Norm Quadratic Average: 30.787797927856445
Nearest Class Center Accuracy: 0.41125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.053310513496398926
Inter Cos: 0.12366215139627457
Norm Quadratic Average: 19.542224884033203
Nearest Class Center Accuracy: 0.439875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06239113211631775
Inter Cos: 0.12151658535003662
Norm Quadratic Average: 17.713851928710938
Nearest Class Center Accuracy: 0.465375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08207285404205322
Inter Cos: 0.13801410794258118
Norm Quadratic Average: 9.676631927490234
Nearest Class Center Accuracy: 0.51175

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11153235286474228
Inter Cos: 0.1577806919813156
Norm Quadratic Average: 7.049116134643555
Nearest Class Center Accuracy: 0.684875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.66585540771484
Linear Weight Rank: 4031
Intra Cos: 0.3037344217300415
Inter Cos: 0.2975426912307739
Norm Quadratic Average: 28.101091384887695
Nearest Class Center Accuracy: 0.963625

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.12468338012695
Linear Weight Rank: 3671
Intra Cos: 0.5825833678245544
Inter Cos: 0.45828598737716675
Norm Quadratic Average: 24.6141414642334
Nearest Class Center Accuracy: 0.998125

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2201852798461914
Linear Weight Rank: 10
Intra Cos: 0.7234417796134949
Inter Cos: 0.5634280443191528
Norm Quadratic Average: 28.821969985961914
Nearest Class Center Accuracy: 0.999375

Output Layer:
Intra Cos: 0.829170286655426
Inter Cos: 0.7170924544334412
Norm Quadratic Average: 35.58372116088867
Nearest Class Center Accuracy: 0.9985

Test Set:
Average Loss: 3.1033837280273437
Accuracy: 0.5965
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25026828050613403, Weights: 0.04706485942006111
NC2 Equiangle: Features: 0.46129853990342884, Weights: 0.1639025476243761
NC3 Self-Duality: 0.4652600884437561
NC4 NCC Mismatch: 0.16700000000000004

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: 0.02578691579401493
Inter Cos: 0.07860103994607925
Norm Quadratic Average: 32.547794342041016
Nearest Class Center Accuracy: 0.319

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03281138837337494
Inter Cos: 0.09256179630756378
Norm Quadratic Average: 25.49417495727539
Nearest Class Center Accuracy: 0.381

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.035418834537267685
Inter Cos: 0.09001297503709793
Norm Quadratic Average: 30.709461212158203
Nearest Class Center Accuracy: 0.438

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04879022762179375
Inter Cos: 0.114293672144413
Norm Quadratic Average: 19.510971069335938
Nearest Class Center Accuracy: 0.453

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.056758638471364975
Inter Cos: 0.11002124845981598
Norm Quadratic Average: 17.705244064331055
Nearest Class Center Accuracy: 0.463

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06717422604560852
Inter Cos: 0.13388775289058685
Norm Quadratic Average: 9.658262252807617
Nearest Class Center Accuracy: 0.474

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0765819102525711
Inter Cos: 0.14676152169704437
Norm Quadratic Average: 6.999878406524658
Nearest Class Center Accuracy: 0.522

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.66585540771484
Linear Weight Rank: 4031
Intra Cos: 0.13627362251281738
Inter Cos: 0.26318395137786865
Norm Quadratic Average: 27.074125289916992
Nearest Class Center Accuracy: 0.576

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.12468338012695
Linear Weight Rank: 3671
Intra Cos: 0.2190362811088562
Inter Cos: 0.39690595865249634
Norm Quadratic Average: 22.982738494873047
Nearest Class Center Accuracy: 0.58

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2201852798461914
Linear Weight Rank: 10
Intra Cos: 0.2553040385246277
Inter Cos: 0.4813159108161926
Norm Quadratic Average: 26.692514419555664
Nearest Class Center Accuracy: 0.5675

Output Layer:
Intra Cos: 0.2939768433570862
Inter Cos: 0.5868803262710571
Norm Quadratic Average: 32.79924392700195
Nearest Class Center Accuracy: 0.535

