Model save path: ./New_Models/bn_True_dataset_CIFAR10_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: 0.01989092119038105
Inter Cos: 0.10477276146411896
Norm Quadratic Average: 27.59718132019043
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018769221380352974
Inter Cos: 0.0724375918507576
Norm Quadratic Average: 15.162246704101562
Nearest Class Center Accuracy: 0.4006

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01956460252404213
Inter Cos: 0.05349348112940788
Norm Quadratic Average: 7.325728893280029
Nearest Class Center Accuracy: 0.53776

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01409366074949503
Inter Cos: 0.04034857451915741
Norm Quadratic Average: 5.912665367126465
Nearest Class Center Accuracy: 0.61292

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019639041274785995
Inter Cos: 0.03679392486810684
Norm Quadratic Average: 3.9531784057617188
Nearest Class Center Accuracy: 0.74266

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031691353768110275
Inter Cos: 0.03355170041322708
Norm Quadratic Average: 2.7513928413391113
Nearest Class Center Accuracy: 0.8576

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13821741938591003
Inter Cos: 0.0741603821516037
Norm Quadratic Average: 2.0555503368377686
Nearest Class Center Accuracy: 0.97072

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.6468731164932251
Inter Cos: 0.11512046307325363
Norm Quadratic Average: 1.33663809299469
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 4.82645320892334
Linear Weight Rank: 4029
Intra Cos: 0.9247788786888123
Inter Cos: -0.034825023263692856
Norm Quadratic Average: 24.87244987487793
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.290998697280884
Linear Weight Rank: 3635
Intra Cos: 0.9713199734687805
Inter Cos: -0.028271978721022606
Norm Quadratic Average: 18.71319007873535
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.635518789291382
Linear Weight Rank: 9
Intra Cos: 0.9682635068893433
Inter Cos: 0.055727142840623856
Norm Quadratic Average: 14.341054916381836
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9860279560089111
Inter Cos: 0.18465673923492432
Norm Quadratic Average: 12.266325950622559
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.6076113260269165
Accuracy: 0.8541
NC1 Within Class Collapse: 3.8307127952575684
NC2 Equinorm: Features: 0.14821197092533112, Weights: 0.012681419961154461
NC2 Equiangle: Features: 0.12237177954779731, Weights: 0.039457064204745824
NC3 Self-Duality: 0.09509124606847763
NC4 NCC Mismatch: 0.02410000000000001

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526073545217514
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550134658813477
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.017696093767881393
Inter Cos: 0.07399777323007584
Norm Quadratic Average: 15.151006698608398
Nearest Class Center Accuracy: 0.4174

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018605364486575127
Inter Cos: 0.05460160970687866
Norm Quadratic Average: 7.329883098602295
Nearest Class Center Accuracy: 0.5433

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.013238423503935337
Inter Cos: 0.04109649360179901
Norm Quadratic Average: 5.919800281524658
Nearest Class Center Accuracy: 0.6178

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01689429022371769
Inter Cos: 0.03780647739768028
Norm Quadratic Average: 3.9551548957824707
Nearest Class Center Accuracy: 0.7091

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024088429287075996
Inter Cos: 0.035000208765268326
Norm Quadratic Average: 2.7364389896392822
Nearest Class Center Accuracy: 0.7641

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09190675616264343
Inter Cos: 0.08214462548494339
Norm Quadratic Average: 2.016355514526367
Nearest Class Center Accuracy: 0.8074

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.32703569531440735
Inter Cos: 0.1882323920726776
Norm Quadratic Average: 1.2442506551742554
Nearest Class Center Accuracy: 0.8465

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 4.82645320892334
Linear Weight Rank: 4029
Intra Cos: 0.5263384580612183
Inter Cos: 0.21847212314605713
Norm Quadratic Average: 22.15514373779297
Nearest Class Center Accuracy: 0.8445

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.290998697280884
Linear Weight Rank: 3635
Intra Cos: 0.5424513816833496
Inter Cos: 0.21119339764118195
Norm Quadratic Average: 16.459592819213867
Nearest Class Center Accuracy: 0.8493

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.635518789291382
Linear Weight Rank: 9
Intra Cos: 0.5423153638839722
Inter Cos: 0.23262642323970795
Norm Quadratic Average: 12.731781959533691
Nearest Class Center Accuracy: 0.8531

Output Layer:
Intra Cos: 0.5829532146453857
Inter Cos: 0.298220157623291
Norm Quadratic Average: 10.873469352722168
Nearest Class Center Accuracy: 0.8532

