Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.007.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: 0.11371058225631714
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: 0.023876942694187164
Inter Cos: 0.10139569640159607
Norm Quadratic Average: 61.80908203125
Nearest Class Center Accuracy: 0.33575

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025961201637983322
Inter Cos: 0.09018847346305847
Norm Quadratic Average: 46.190025329589844
Nearest Class Center Accuracy: 0.37

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022833967581391335
Inter Cos: 0.0721484050154686
Norm Quadratic Average: 49.40485763549805
Nearest Class Center Accuracy: 0.4015

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0313098318874836
Inter Cos: 0.08189398050308228
Norm Quadratic Average: 31.520570755004883
Nearest Class Center Accuracy: 0.42425

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030302129685878754
Inter Cos: 0.06835271418094635
Norm Quadratic Average: 32.136043548583984
Nearest Class Center Accuracy: 0.46875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04293990880250931
Inter Cos: 0.0738820806145668
Norm Quadratic Average: 20.411821365356445
Nearest Class Center Accuracy: 0.597125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07650396972894669
Inter Cos: 0.08036559820175171
Norm Quadratic Average: 14.367950439453125
Nearest Class Center Accuracy: 0.928375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46304321289062
Linear Weight Rank: 4031
Intra Cos: 0.25918421149253845
Inter Cos: 0.12405449897050858
Norm Quadratic Average: 81.85989379882812
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.2987003326416
Linear Weight Rank: 3670
Intra Cos: 0.5739017128944397
Inter Cos: 0.24410328269004822
Norm Quadratic Average: 39.44386291503906
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.0317671298980713
Linear Weight Rank: 10
Intra Cos: 0.7849171757698059
Inter Cos: 0.3404252529144287
Norm Quadratic Average: 26.122222900390625
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8977035284042358
Inter Cos: 0.46378254890441895
Norm Quadratic Average: 16.870187759399414
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.8068276405334474
Accuracy: 0.5785
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2149963527917862, Weights: 0.012391149997711182
NC2 Equiangle: Features: 0.4260150485568576, Weights: 0.09937405056423611
NC3 Self-Duality: 0.5494744777679443
NC4 NCC Mismatch: 0.15300000000000002

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.53066635131836
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023080529645085335
Inter Cos: 0.08744226396083832
Norm Quadratic Average: 61.453285217285156
Nearest Class Center Accuracy: 0.35

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02616976574063301
Inter Cos: 0.07805878669023514
Norm Quadratic Average: 45.94838333129883
Nearest Class Center Accuracy: 0.4

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023022504523396492
Inter Cos: 0.06269656121730804
Norm Quadratic Average: 49.230045318603516
Nearest Class Center Accuracy: 0.434

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029531167820096016
Inter Cos: 0.07064435631036758
Norm Quadratic Average: 31.411108016967773
Nearest Class Center Accuracy: 0.448

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02752346731722355
Inter Cos: 0.05883081629872322
Norm Quadratic Average: 32.059444427490234
Nearest Class Center Accuracy: 0.483

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030811263248324394
Inter Cos: 0.0707809329032898
Norm Quadratic Average: 20.328901290893555
Nearest Class Center Accuracy: 0.5085

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034884262830019
Inter Cos: 0.07192479074001312
Norm Quadratic Average: 14.2225341796875
Nearest Class Center Accuracy: 0.5875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.46304321289062
Linear Weight Rank: 4031
Intra Cos: 0.07001816481351852
Inter Cos: 0.13104888796806335
Norm Quadratic Average: 77.86727142333984
Nearest Class Center Accuracy: 0.6105

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.2987003326416
Linear Weight Rank: 3670
Intra Cos: 0.14733295142650604
Inter Cos: 0.25976455211639404
Norm Quadratic Average: 35.39181900024414
Nearest Class Center Accuracy: 0.5855

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.0317671298980713
Linear Weight Rank: 10
Intra Cos: 0.2059454619884491
Inter Cos: 0.3709842562675476
Norm Quadratic Average: 22.656396865844727
Nearest Class Center Accuracy: 0.5785

Output Layer:
Intra Cos: 0.24958565831184387
Inter Cos: 0.48485663533210754
Norm Quadratic Average: 14.366971969604492
Nearest Class Center Accuracy: 0.57

