Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.0003.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: 0.023371923714876175
Inter Cos: 0.0786571130156517
Norm Quadratic Average: 87.6918716430664
Nearest Class Center Accuracy: 0.34475

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030118875205516815
Inter Cos: 0.08395357429981232
Norm Quadratic Average: 65.39679718017578
Nearest Class Center Accuracy: 0.374875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025382844731211662
Inter Cos: 0.06398709863424301
Norm Quadratic Average: 68.42243194580078
Nearest Class Center Accuracy: 0.40575

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03514479845762253
Inter Cos: 0.07942581176757812
Norm Quadratic Average: 44.085052490234375
Nearest Class Center Accuracy: 0.4265

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032969892024993896
Inter Cos: 0.06099332123994827
Norm Quadratic Average: 44.74436569213867
Nearest Class Center Accuracy: 0.465375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04697006940841675
Inter Cos: 0.07675784826278687
Norm Quadratic Average: 28.781770706176758
Nearest Class Center Accuracy: 0.550125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06319606304168701
Inter Cos: 0.0753762423992157
Norm Quadratic Average: 20.260665893554688
Nearest Class Center Accuracy: 0.838375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.9446792602539
Linear Weight Rank: 4031
Intra Cos: 0.1788201928138733
Inter Cos: 0.0999598428606987
Norm Quadratic Average: 107.750244140625
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.4021110534668
Linear Weight Rank: 3671
Intra Cos: 0.4035997688770294
Inter Cos: 0.18774135410785675
Norm Quadratic Average: 56.15816879272461
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5030179023742676
Linear Weight Rank: 10
Intra Cos: 0.626971423625946
Inter Cos: 0.2997857630252838
Norm Quadratic Average: 39.056861877441406
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8603976368904114
Inter Cos: 0.5292211174964905
Norm Quadratic Average: 26.565507888793945
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.6446919174194337
Accuracy: 0.5965
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21323131024837494, Weights: 0.021257491782307625
NC2 Equiangle: Features: 0.4402544657389323, Weights: 0.08448673884073893
NC3 Self-Duality: 0.6390666961669922
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: 0.022941524162888527
Inter Cos: 0.07398149371147156
Norm Quadratic Average: 87.49007415771484
Nearest Class Center Accuracy: 0.362

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02979130484163761
Inter Cos: 0.08167809247970581
Norm Quadratic Average: 65.23223876953125
Nearest Class Center Accuracy: 0.406

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02441648207604885
Inter Cos: 0.060003750026226044
Norm Quadratic Average: 68.2906723022461
Nearest Class Center Accuracy: 0.4415

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031816307455301285
Inter Cos: 0.07890152186155319
Norm Quadratic Average: 43.98383331298828
Nearest Class Center Accuracy: 0.4475

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028821656480431557
Inter Cos: 0.05909039080142975
Norm Quadratic Average: 44.59850311279297
Nearest Class Center Accuracy: 0.47

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.035443007946014404
Inter Cos: 0.07593737542629242
Norm Quadratic Average: 28.632152557373047
Nearest Class Center Accuracy: 0.4875

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03751932457089424
Inter Cos: 0.06553498655557632
Norm Quadratic Average: 20.066152572631836
Nearest Class Center Accuracy: 0.569

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.9446792602539
Linear Weight Rank: 4031
Intra Cos: 0.06280739605426788
Inter Cos: 0.10015781968832016
Norm Quadratic Average: 103.91547393798828
Nearest Class Center Accuracy: 0.622

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.4021110534668
Linear Weight Rank: 3671
Intra Cos: 0.12211018055677414
Inter Cos: 0.1939464807510376
Norm Quadratic Average: 52.111995697021484
Nearest Class Center Accuracy: 0.5955

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5030179023742676
Linear Weight Rank: 10
Intra Cos: 0.18738064169883728
Inter Cos: 0.30907270312309265
Norm Quadratic Average: 35.043792724609375
Nearest Class Center Accuracy: 0.5885

Output Layer:
Intra Cos: 0.2739914059638977
Inter Cos: 0.49108830094337463
Norm Quadratic Average: 23.2453670501709
Nearest Class Center Accuracy: 0.573

