Model save path: ./New_Models/bn_True_dataset_CIFAR100_epochs_200_lr_0.01_model_type_vgg11_rand_seed_314159_test_samples_None_train_samples_None_weight_decay_0.0005.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: 0.026649996638298035
Inter Cos: 0.02767673134803772
Norm Quadratic Average: 28.694026947021484
Nearest Class Center Accuracy: 0.04894

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022867344319820404
Inter Cos: 0.021674472838640213
Norm Quadratic Average: 14.776704788208008
Nearest Class Center Accuracy: 0.06048

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01795217953622341
Inter Cos: 0.01918775402009487
Norm Quadratic Average: 12.401908874511719
Nearest Class Center Accuracy: 0.06852

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02457115799188614
Inter Cos: 0.02157655917108059
Norm Quadratic Average: 7.874233722686768
Nearest Class Center Accuracy: 0.07868

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02926027774810791
Inter Cos: 0.02558145485818386
Norm Quadratic Average: 6.593971252441406
Nearest Class Center Accuracy: 0.0846

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06963871419429779
Inter Cos: 0.05074133723974228
Norm Quadratic Average: 4.5057878494262695
Nearest Class Center Accuracy: 0.09646

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.26521581411361694
Inter Cos: 0.1354799121618271
Norm Quadratic Average: 3.5014753341674805
Nearest Class Center Accuracy: 0.09994

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 21.721467971801758
Linear Weight Rank: 4029
Intra Cos: 0.6559256911277771
Inter Cos: 0.20665735006332397
Norm Quadratic Average: 36.847476959228516
Nearest Class Center Accuracy: 0.1

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 12.23602294921875
Linear Weight Rank: 3641
Intra Cos: 0.8301329612731934
Inter Cos: 0.2315710484981537
Norm Quadratic Average: 30.588136672973633
Nearest Class Center Accuracy: 0.1

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 8.507177352905273
Linear Weight Rank: 98
Intra Cos: 0.867767870426178
Inter Cos: 0.27379265427589417
Norm Quadratic Average: 31.070363998413086
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.9046229124069214
Inter Cos: 0.41424107551574707
Norm Quadratic Average: 43.789485931396484
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 2.5076527862548827
Accuracy: 0.5478
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2491287887096405, Weights: 0.0334138385951519
NC2 Equiangle: Features: 0.17959613222064394, Weights: 0.09794500177556818
NC3 Self-Duality: 0.41760408878326416
NC4 NCC Mismatch: 0.15380000000000005

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: 0.013625995256006718
Inter Cos: 0.2509099841117859
Norm Quadratic Average: 28.89704704284668
Nearest Class Center Accuracy: 0.2675

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.016378004103899002
Inter Cos: 0.19759446382522583
Norm Quadratic Average: 14.885018348693848
Nearest Class Center Accuracy: 0.3918

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.014201519079506397
Inter Cos: 0.14545544981956482
Norm Quadratic Average: 12.45626163482666
Nearest Class Center Accuracy: 0.5041

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.014482970349490643
Inter Cos: 0.13625362515449524
Norm Quadratic Average: 7.890659809112549
Nearest Class Center Accuracy: 0.5973

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.013503548689186573
Inter Cos: 0.12599223852157593
Norm Quadratic Average: 6.574196815490723
Nearest Class Center Accuracy: 0.6327

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023252833634614944
Inter Cos: 0.16770119965076447
Norm Quadratic Average: 4.432061195373535
Nearest Class Center Accuracy: 0.6245

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0624082125723362
Inter Cos: 0.344405859708786
Norm Quadratic Average: 3.2378296852111816
Nearest Class Center Accuracy: 0.5897

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 21.721467971801758
Linear Weight Rank: 4029
Intra Cos: 0.17176750302314758
Inter Cos: 0.4688089191913605
Norm Quadratic Average: 30.75328826904297
Nearest Class Center Accuracy: 0.5438

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 12.23602294921875
Linear Weight Rank: 3641
Intra Cos: 0.18908007442951202
Inter Cos: 0.4843117296695709
Norm Quadratic Average: 24.54986572265625
Nearest Class Center Accuracy: 0.5493

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 8.507177352905273
Linear Weight Rank: 98
Intra Cos: 0.1890534907579422
Inter Cos: 0.5537379384040833
Norm Quadratic Average: 25.12240219116211
Nearest Class Center Accuracy: 0.5469

Output Layer:
Intra Cos: 0.20137274265289307
Inter Cos: 0.6437232494354248
Norm Quadratic Average: 35.67129135131836
Nearest Class Center Accuracy: 0.5419

