Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.01.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: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02290092594921589
Inter Cos: 0.09730354696512222
Norm Quadratic Average: 54.984493255615234
Nearest Class Center Accuracy: 0.3515

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02599387802183628
Inter Cos: 0.09376392513513565
Norm Quadratic Average: 40.83229064941406
Nearest Class Center Accuracy: 0.378875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023023977875709534
Inter Cos: 0.06730423867702484
Norm Quadratic Average: 43.279808044433594
Nearest Class Center Accuracy: 0.413875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031202584505081177
Inter Cos: 0.07798565924167633
Norm Quadratic Average: 27.246109008789062
Nearest Class Center Accuracy: 0.440375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03207622468471527
Inter Cos: 0.0722765251994133
Norm Quadratic Average: 27.779380798339844
Nearest Class Center Accuracy: 0.495625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04842374846339226
Inter Cos: 0.08165622502565384
Norm Quadratic Average: 17.515344619750977
Nearest Class Center Accuracy: 0.638875

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09432344138622284
Inter Cos: 0.08624535799026489
Norm Quadratic Average: 12.292807579040527
Nearest Class Center Accuracy: 0.963875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.74006652832031
Linear Weight Rank: 4031
Intra Cos: 0.3315040171146393
Inter Cos: 0.13390372693538666
Norm Quadratic Average: 75.06798553466797
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.382518768310547
Linear Weight Rank: 3670
Intra Cos: 0.6804149150848389
Inter Cos: 0.2499047815799713
Norm Quadratic Average: 35.737274169921875
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.9026662111282349
Linear Weight Rank: 10
Intra Cos: 0.8398696184158325
Inter Cos: 0.319598913192749
Norm Quadratic Average: 23.38022232055664
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9088459014892578
Inter Cos: 0.4118139147758484
Norm Quadratic Average: 14.95430850982666
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.6127239837646485
Accuracy: 0.587
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20313408970832825, Weights: 0.01755809597671032
NC2 Equiangle: Features: 0.40601289537217883, Weights: 0.1103477054172092
NC3 Self-Duality: 0.49355798959732056
NC4 NCC Mismatch: 0.13149999999999995

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
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: 0.02260866016149521
Inter Cos: 0.08552362769842148
Norm Quadratic Average: 54.731109619140625
Nearest Class Center Accuracy: 0.371

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025682643055915833
Inter Cos: 0.08303111791610718
Norm Quadratic Average: 40.62508773803711
Nearest Class Center Accuracy: 0.4025

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02164936251938343
Inter Cos: 0.0596739798784256
Norm Quadratic Average: 43.13187026977539
Nearest Class Center Accuracy: 0.451

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02706158347427845
Inter Cos: 0.0689263716340065
Norm Quadratic Average: 27.14047622680664
Nearest Class Center Accuracy: 0.4595

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027219949290156364
Inter Cos: 0.0634283572435379
Norm Quadratic Average: 27.708925247192383
Nearest Class Center Accuracy: 0.506

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03324039652943611
Inter Cos: 0.07104791700839996
Norm Quadratic Average: 17.432456970214844
Nearest Class Center Accuracy: 0.5315

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04233863949775696
Inter Cos: 0.08621691167354584
Norm Quadratic Average: 12.150348663330078
Nearest Class Center Accuracy: 0.6045

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.74006652832031
Linear Weight Rank: 4031
Intra Cos: 0.09580107778310776
Inter Cos: 0.1652688831090927
Norm Quadratic Average: 70.44795227050781
Nearest Class Center Accuracy: 0.604

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.382518768310547
Linear Weight Rank: 3670
Intra Cos: 0.1919124871492386
Inter Cos: 0.3049445152282715
Norm Quadratic Average: 31.299489974975586
Nearest Class Center Accuracy: 0.5895

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.9026662111282349
Linear Weight Rank: 10
Intra Cos: 0.2487882673740387
Inter Cos: 0.40032052993774414
Norm Quadratic Average: 19.83924102783203
Nearest Class Center Accuracy: 0.582

Output Layer:
Intra Cos: 0.27813196182250977
Inter Cos: 0.4775070548057556
Norm Quadratic Average: 12.49803352355957
Nearest Class Center Accuracy: 0.571

