Model save path: ./New_Models/bn_False_dataset_CIFAR100_epochs_200_lr_0.01_model_type_vgg11_rand_seed_314159_test_samples_None_train_samples_None_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: 0.022893192246556282
Inter Cos: 0.07011394202709198
Norm Quadratic Average: 29.326322555541992
Nearest Class Center Accuracy: 0.03258

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03674810379743576
Inter Cos: 0.06332569569349289
Norm Quadratic Average: 36.34501647949219
Nearest Class Center Accuracy: 0.04354

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04544702544808388
Inter Cos: 0.041360870003700256
Norm Quadratic Average: 46.3547477722168
Nearest Class Center Accuracy: 0.05166

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03671137988567352
Inter Cos: 0.038007114082574844
Norm Quadratic Average: 77.79056549072266
Nearest Class Center Accuracy: 0.06168

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036229804158210754
Inter Cos: 0.031727682799100876
Norm Quadratic Average: 49.884681701660156
Nearest Class Center Accuracy: 0.07002

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03377441316843033
Inter Cos: 0.02935405820608139
Norm Quadratic Average: 28.383256912231445
Nearest Class Center Accuracy: 0.07506

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07839557528495789
Inter Cos: 0.05176324397325516
Norm Quadratic Average: 9.388894081115723
Nearest Class Center Accuracy: 0.08414

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.36786165833473206
Inter Cos: 0.1925133764743805
Norm Quadratic Average: 4.551999092102051
Nearest Class Center Accuracy: 0.09918

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 7.154140472412109
Linear Weight Rank: 4024
Intra Cos: 0.6569008231163025
Inter Cos: 0.32803159952163696
Norm Quadratic Average: 27.855525970458984
Nearest Class Center Accuracy: 0.1

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 7.107607364654541
Linear Weight Rank: 3590
Intra Cos: 0.6859706044197083
Inter Cos: 0.3382205367088318
Norm Quadratic Average: 35.182289123535156
Nearest Class Center Accuracy: 0.1

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 7.209218502044678
Linear Weight Rank: 98
Intra Cos: 0.6881643533706665
Inter Cos: 0.3341789245605469
Norm Quadratic Average: 43.32588577270508
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.7197228670120239
Inter Cos: 0.3862243890762329
Norm Quadratic Average: 64.12762451171875
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 3.5999122032165527
Accuracy: 0.4669
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23997612297534943, Weights: 0.034078389406204224
NC2 Equiangle: Features: 0.23640876538825759, Weights: 0.1265106016216856
NC3 Self-Duality: 0.4724104106426239
NC4 NCC Mismatch: 0.25860000000000005

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.006621268577873707
Inter Cos: 0.4067547917366028
Norm Quadratic Average: 29.42218780517578
Nearest Class Center Accuracy: 0.1136

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.015566942282021046
Inter Cos: 0.31253787875175476
Norm Quadratic Average: 36.54985809326172
Nearest Class Center Accuracy: 0.2212

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024358339607715607
Inter Cos: 0.34449315071105957
Norm Quadratic Average: 46.62846755981445
Nearest Class Center Accuracy: 0.2753

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024316709488630295
Inter Cos: 0.31631767749786377
Norm Quadratic Average: 78.34285736083984
Nearest Class Center Accuracy: 0.3446

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023260701447725296
Inter Cos: 0.2433985322713852
Norm Quadratic Average: 50.32698059082031
Nearest Class Center Accuracy: 0.4446

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021610736846923828
Inter Cos: 0.1623927801847458
Norm Quadratic Average: 28.56550407409668
Nearest Class Center Accuracy: 0.5068

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031794607639312744
Inter Cos: 0.2550778090953827
Norm Quadratic Average: 9.3551025390625
Nearest Class Center Accuracy: 0.4991

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08736960589885712
Inter Cos: 0.5051094889640808
Norm Quadratic Average: 4.407361030578613
Nearest Class Center Accuracy: 0.4984

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 7.154140472412109
Linear Weight Rank: 4024
Intra Cos: 0.12122263759374619
Inter Cos: 0.6103346347808838
Norm Quadratic Average: 25.966915130615234
Nearest Class Center Accuracy: 0.4754

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 7.107607364654541
Linear Weight Rank: 3590
Intra Cos: 0.12287821620702744
Inter Cos: 0.613638699054718
Norm Quadratic Average: 32.72434616088867
Nearest Class Center Accuracy: 0.4699

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 7.209218502044678
Linear Weight Rank: 98
Intra Cos: 0.12363281100988388
Inter Cos: 0.6069283485412598
Norm Quadratic Average: 40.55939865112305
Nearest Class Center Accuracy: 0.4681

Output Layer:
Intra Cos: 0.12593422830104828
Inter Cos: 0.6636194586753845
Norm Quadratic Average: 60.13580322265625
Nearest Class Center Accuracy: 0.4597

