Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.0007.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691621780395508
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026789696887135506
Inter Cos: 0.10102295875549316
Norm Quadratic Average: 84.3516845703125
Nearest Class Center Accuracy: 0.341125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031112201511859894
Inter Cos: 0.08962531387805939
Norm Quadratic Average: 61.53994369506836
Nearest Class Center Accuracy: 0.375125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02700108103454113
Inter Cos: 0.07033126801252365
Norm Quadratic Average: 66.89138793945312
Nearest Class Center Accuracy: 0.407375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03406592831015587
Inter Cos: 0.07804061472415924
Norm Quadratic Average: 42.662288665771484
Nearest Class Center Accuracy: 0.428875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03353595361113548
Inter Cos: 0.0667874664068222
Norm Quadratic Average: 43.59478759765625
Nearest Class Center Accuracy: 0.465875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0461142435669899
Inter Cos: 0.07882540673017502
Norm Quadratic Average: 28.094234466552734
Nearest Class Center Accuracy: 0.552

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05974079295992851
Inter Cos: 0.07570602744817734
Norm Quadratic Average: 19.69696807861328
Nearest Class Center Accuracy: 0.831625

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.04290771484375
Linear Weight Rank: 4031
Intra Cos: 0.18151994049549103
Inter Cos: 0.10449811816215515
Norm Quadratic Average: 105.29946899414062
Nearest Class Center Accuracy: 0.999875

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.639339447021484
Linear Weight Rank: 3671
Intra Cos: 0.42488202452659607
Inter Cos: 0.18310554325580597
Norm Quadratic Average: 54.77341842651367
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.488466501235962
Linear Weight Rank: 10
Intra Cos: 0.6646364331245422
Inter Cos: 0.2727625072002411
Norm Quadratic Average: 38.04710388183594
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8831683993339539
Inter Cos: 0.5032117366790771
Norm Quadratic Average: 26.388607025146484
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.5920650405883787
Accuracy: 0.584
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21073555946350098, Weights: 0.019986117258667946
NC2 Equiangle: Features: 0.45136227077907987, Weights: 0.08715684678819445
NC3 Self-Duality: 0.6358317136764526
NC4 NCC Mismatch: 0.14100000000000001

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352368116378784
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: 0.024577371776103973
Inter Cos: 0.0888281986117363
Norm Quadratic Average: 84.33792877197266
Nearest Class Center Accuracy: 0.354

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029709579423069954
Inter Cos: 0.0867607444524765
Norm Quadratic Average: 61.56244659423828
Nearest Class Center Accuracy: 0.394

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026472413912415504
Inter Cos: 0.06534785032272339
Norm Quadratic Average: 66.95873260498047
Nearest Class Center Accuracy: 0.426

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03182007372379303
Inter Cos: 0.07926364988088608
Norm Quadratic Average: 42.66948318481445
Nearest Class Center Accuracy: 0.443

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03068777732551098
Inter Cos: 0.06707973778247833
Norm Quadratic Average: 43.570926666259766
Nearest Class Center Accuracy: 0.4705

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03546624258160591
Inter Cos: 0.07834937423467636
Norm Quadratic Average: 28.0248966217041
Nearest Class Center Accuracy: 0.4835

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03407936915755272
Inter Cos: 0.07042651623487473
Norm Quadratic Average: 19.540456771850586
Nearest Class Center Accuracy: 0.5735

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.04290771484375
Linear Weight Rank: 4031
Intra Cos: 0.05723043531179428
Inter Cos: 0.10677327960729599
Norm Quadratic Average: 101.36715698242188
Nearest Class Center Accuracy: 0.6165

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.639339447021484
Linear Weight Rank: 3671
Intra Cos: 0.11807971447706223
Inter Cos: 0.19423700869083405
Norm Quadratic Average: 50.38979721069336
Nearest Class Center Accuracy: 0.5965

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.488466501235962
Linear Weight Rank: 10
Intra Cos: 0.1843651384115219
Inter Cos: 0.30275654792785645
Norm Quadratic Average: 33.67828369140625
Nearest Class Center Accuracy: 0.578

Output Layer:
Intra Cos: 0.27122387290000916
Inter Cos: 0.47376012802124023
Norm Quadratic Average: 22.65453338623047
Nearest Class Center Accuracy: 0.5635

