Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_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: 0.021450398489832878
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: 0.0246086735278368
Inter Cos: 0.09608705341815948
Norm Quadratic Average: 32.5361328125
Nearest Class Center Accuracy: 0.303625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03101440891623497
Inter Cos: 0.10128308832645416
Norm Quadratic Average: 25.37259292602539
Nearest Class Center Accuracy: 0.369875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034957077354192734
Inter Cos: 0.09731123596429825
Norm Quadratic Average: 30.67778205871582
Nearest Class Center Accuracy: 0.41225

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05208443105220795
Inter Cos: 0.1224924623966217
Norm Quadratic Average: 19.46950912475586
Nearest Class Center Accuracy: 0.44

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.060894113034009933
Inter Cos: 0.11977998912334442
Norm Quadratic Average: 17.734643936157227
Nearest Class Center Accuracy: 0.464625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0821390226483345
Inter Cos: 0.13611586391925812
Norm Quadratic Average: 9.701648712158203
Nearest Class Center Accuracy: 0.513625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11079099774360657
Inter Cos: 0.15586324036121368
Norm Quadratic Average: 7.15634298324585
Nearest Class Center Accuracy: 0.692375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.0657730102539
Linear Weight Rank: 4031
Intra Cos: 0.3136653006076813
Inter Cos: 0.2910338342189789
Norm Quadratic Average: 28.789411544799805
Nearest Class Center Accuracy: 0.967625

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.688472747802734
Linear Weight Rank: 3671
Intra Cos: 0.5968782901763916
Inter Cos: 0.44282108545303345
Norm Quadratic Average: 25.115859985351562
Nearest Class Center Accuracy: 0.998375

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2264931201934814
Linear Weight Rank: 10
Intra Cos: 0.7387788891792297
Inter Cos: 0.5448932647705078
Norm Quadratic Average: 29.272783279418945
Nearest Class Center Accuracy: 0.9995

Output Layer:
Intra Cos: 0.8439483046531677
Inter Cos: 0.6963211894035339
Norm Quadratic Average: 35.80896759033203
Nearest Class Center Accuracy: 0.9985

Test Set:
Average Loss: 3.1761045837402344
Accuracy: 0.5895
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2438662201166153, Weights: 0.044638197869062424
NC2 Equiangle: Features: 0.4492731730143229, Weights: 0.16212677425808378
NC3 Self-Duality: 0.45733726024627686
NC4 NCC Mismatch: 0.16100000000000003

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
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: 0.025884194299578667
Inter Cos: 0.079018235206604
Norm Quadratic Average: 32.3169059753418
Nearest Class Center Accuracy: 0.321

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03222915902733803
Inter Cos: 0.0911758616566658
Norm Quadratic Average: 25.24803924560547
Nearest Class Center Accuracy: 0.3845

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03463335707783699
Inter Cos: 0.08963411301374435
Norm Quadratic Average: 30.595447540283203
Nearest Class Center Accuracy: 0.4355

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04797324910759926
Inter Cos: 0.11523524671792984
Norm Quadratic Average: 19.4399356842041
Nearest Class Center Accuracy: 0.453

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.055334072560071945
Inter Cos: 0.10863036662340164
Norm Quadratic Average: 17.723684310913086
Nearest Class Center Accuracy: 0.4625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06643650680780411
Inter Cos: 0.13018004596233368
Norm Quadratic Average: 9.685632705688477
Nearest Class Center Accuracy: 0.4765

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07384408265352249
Inter Cos: 0.14586122334003448
Norm Quadratic Average: 7.109212875366211
Nearest Class Center Accuracy: 0.528

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.0657730102539
Linear Weight Rank: 4031
Intra Cos: 0.1345788836479187
Inter Cos: 0.2593749761581421
Norm Quadratic Average: 27.717912673950195
Nearest Class Center Accuracy: 0.584

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.688472747802734
Linear Weight Rank: 3671
Intra Cos: 0.21459650993347168
Inter Cos: 0.3872464597225189
Norm Quadratic Average: 23.43523597717285
Nearest Class Center Accuracy: 0.587

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2264931201934814
Linear Weight Rank: 10
Intra Cos: 0.250475138425827
Inter Cos: 0.47019708156585693
Norm Quadratic Average: 27.0847110748291
Nearest Class Center Accuracy: 0.566

Output Layer:
Intra Cos: 0.28790730237960815
Inter Cos: 0.5744280219078064
Norm Quadratic Average: 32.97113800048828
Nearest Class Center Accuracy: 0.533

