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_0.001.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: 0.025534160435199738
Inter Cos: 0.02937115728855133
Norm Quadratic Average: 20.149246215820312
Nearest Class Center Accuracy: 0.04902

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021691802889108658
Inter Cos: 0.022618360817432404
Norm Quadratic Average: 10.259479522705078
Nearest Class Center Accuracy: 0.06036

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01738573983311653
Inter Cos: 0.018786348402500153
Norm Quadratic Average: 8.382731437683105
Nearest Class Center Accuracy: 0.06868

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023591935634613037
Inter Cos: 0.020548410713672638
Norm Quadratic Average: 5.599331378936768
Nearest Class Center Accuracy: 0.07944

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02660507522523403
Inter Cos: 0.024416249245405197
Norm Quadratic Average: 4.16062593460083
Nearest Class Center Accuracy: 0.0854

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07066691666841507
Inter Cos: 0.04856787621974945
Norm Quadratic Average: 2.89319109916687
Nearest Class Center Accuracy: 0.09752

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.29931479692459106
Inter Cos: 0.13217534124851227
Norm Quadratic Average: 1.6767922639846802
Nearest Class Center Accuracy: 0.1

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 7.363047122955322
Linear Weight Rank: 4020
Intra Cos: 0.757551372051239
Inter Cos: 0.225116565823555
Norm Quadratic Average: 38.2281379699707
Nearest Class Center Accuracy: 0.1

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 6.945175647735596
Linear Weight Rank: 3519
Intra Cos: 0.8632072806358337
Inter Cos: 0.30297210812568665
Norm Quadratic Average: 31.570627212524414
Nearest Class Center Accuracy: 0.1

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 6.751588344573975
Linear Weight Rank: 98
Intra Cos: 0.8802451491355896
Inter Cos: 0.3396987020969391
Norm Quadratic Average: 31.1777286529541
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.9041565656661987
Inter Cos: 0.38123762607574463
Norm Quadratic Average: 37.79384994506836
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 2.0730258724212645
Accuracy: 0.557
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2377939522266388, Weights: 0.025638222694396973
NC2 Equiangle: Features: 0.18824926511205808, Weights: 0.10712143406723484
NC3 Self-Duality: 0.37485674023628235
NC4 NCC Mismatch: 0.15849999999999997

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: 0.013809909112751484
Inter Cos: 0.2545623183250427
Norm Quadratic Average: 20.291624069213867
Nearest Class Center Accuracy: 0.2673

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.016084007918834686
Inter Cos: 0.19737508893013
Norm Quadratic Average: 10.339083671569824
Nearest Class Center Accuracy: 0.3949

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.014116206206381321
Inter Cos: 0.13805967569351196
Norm Quadratic Average: 8.420950889587402
Nearest Class Center Accuracy: 0.5125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01301496010273695
Inter Cos: 0.13699224591255188
Norm Quadratic Average: 5.613648414611816
Nearest Class Center Accuracy: 0.6115

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.011478851549327374
Inter Cos: 0.11893493682146072
Norm Quadratic Average: 4.144913673400879
Nearest Class Center Accuracy: 0.6553

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02062225714325905
Inter Cos: 0.17162008583545685
Norm Quadratic Average: 2.828960657119751
Nearest Class Center Accuracy: 0.6468

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05271454527974129
Inter Cos: 0.3257492780685425
Norm Quadratic Average: 1.4987736940383911
Nearest Class Center Accuracy: 0.603

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 7.363047122955322
Linear Weight Rank: 4020
Intra Cos: 0.1905754804611206
Inter Cos: 0.4433850049972534
Norm Quadratic Average: 30.421113967895508
Nearest Class Center Accuracy: 0.561

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 6.945175647735596
Linear Weight Rank: 3519
Intra Cos: 0.2143033891916275
Inter Cos: 0.49193209409713745
Norm Quadratic Average: 24.83492088317871
Nearest Class Center Accuracy: 0.5603

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 6.751588344573975
Linear Weight Rank: 98
Intra Cos: 0.21337643265724182
Inter Cos: 0.529535710811615
Norm Quadratic Average: 25.048280715942383
Nearest Class Center Accuracy: 0.5596

Output Layer:
Intra Cos: 0.21738088130950928
Inter Cos: 0.5875394940376282
Norm Quadratic Average: 30.63589096069336
Nearest Class Center Accuracy: 0.5567

