Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_979323_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: 0.0198909230530262
Inter Cos: 0.10477276891469955
Norm Quadratic Average: 27.59718894958496
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02517894096672535
Inter Cos: 0.09984523057937622
Norm Quadratic Average: 25.361082077026367
Nearest Class Center Accuracy: 0.38284

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029116759076714516
Inter Cos: 0.09589821845293045
Norm Quadratic Average: 24.149892807006836
Nearest Class Center Accuracy: 0.4629

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029611753299832344
Inter Cos: 0.07844466716051102
Norm Quadratic Average: 29.33089828491211
Nearest Class Center Accuracy: 0.5417

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031270865350961685
Inter Cos: 0.05987868830561638
Norm Quadratic Average: 14.422355651855469
Nearest Class Center Accuracy: 0.63546

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05172784626483917
Inter Cos: 0.06359931826591492
Norm Quadratic Average: 8.078091621398926
Nearest Class Center Accuracy: 0.7097

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.14756806194782257
Inter Cos: 0.18788066506385803
Norm Quadratic Average: 2.840237617492676
Nearest Class Center Accuracy: 0.84942

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5555241703987122
Inter Cos: 0.3400135934352875
Norm Quadratic Average: 1.6071934700012207
Nearest Class Center Accuracy: 0.99492

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 5.404858589172363
Linear Weight Rank: 4028
Intra Cos: 0.7529391050338745
Inter Cos: 0.2905326783657074
Norm Quadratic Average: 10.902584075927734
Nearest Class Center Accuracy: 0.99822

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 4.060352802276611
Linear Weight Rank: 3644
Intra Cos: 0.8259062767028809
Inter Cos: 0.2338671088218689
Norm Quadratic Average: 11.63944149017334
Nearest Class Center Accuracy: 0.9997

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.6076273918151855
Linear Weight Rank: 9
Intra Cos: 0.8433908224105835
Inter Cos: 0.21368619799613953
Norm Quadratic Average: 12.718672752380371
Nearest Class Center Accuracy: 0.99998

Output Layer:
Intra Cos: 0.8652153015136719
Inter Cos: 0.28108036518096924
Norm Quadratic Average: 15.422550201416016
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.8623388810634613
Accuracy: 0.8113
NC1 Within Class Collapse: 6.184781074523926
NC2 Equinorm: Features: 0.2126430720090866, Weights: 0.04211894050240517
NC2 Equiangle: Features: 0.20954000684950086, Weights: 0.05216483540005154
NC3 Self-Duality: 0.15800631046295166
NC4 NCC Mismatch: 0.04800000000000004

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526077270507812
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550140380859375
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023395659402012825
Inter Cos: 0.10063207894563675
Norm Quadratic Average: 25.34659767150879
Nearest Class Center Accuracy: 0.3991

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02767646312713623
Inter Cos: 0.09768931567668915
Norm Quadratic Average: 24.156890869140625
Nearest Class Center Accuracy: 0.472

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027684805914759636
Inter Cos: 0.07944951206445694
Norm Quadratic Average: 29.354745864868164
Nearest Class Center Accuracy: 0.5465

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028042232617735863
Inter Cos: 0.06090668588876724
Norm Quadratic Average: 14.442992210388184
Nearest Class Center Accuracy: 0.6258

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0456361323595047
Inter Cos: 0.06535616517066956
Norm Quadratic Average: 8.081229209899902
Nearest Class Center Accuracy: 0.6796

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12707304954528809
Inter Cos: 0.188873291015625
Norm Quadratic Average: 2.834275484085083
Nearest Class Center Accuracy: 0.745

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3668511211872101
Inter Cos: 0.3472279906272888
Norm Quadratic Average: 1.5797381401062012
Nearest Class Center Accuracy: 0.8018

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 5.404858589172363
Linear Weight Rank: 4028
Intra Cos: 0.4685686230659485
Inter Cos: 0.35143452882766724
Norm Quadratic Average: 10.594901084899902
Nearest Class Center Accuracy: 0.8009

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 4.060352802276611
Linear Weight Rank: 3644
Intra Cos: 0.4836767017841339
Inter Cos: 0.33370861411094666
Norm Quadratic Average: 11.222886085510254
Nearest Class Center Accuracy: 0.8033

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.6076273918151855
Linear Weight Rank: 9
Intra Cos: 0.4688895642757416
Inter Cos: 0.3082558214664459
Norm Quadratic Average: 12.2139892578125
Nearest Class Center Accuracy: 0.8039

Output Layer:
Intra Cos: 0.47321033477783203
Inter Cos: 0.31938618421554565
Norm Quadratic Average: 14.762869834899902
Nearest Class Center Accuracy: 0.8056

