Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_test_samples_None_train_samples_None_weight_decay_0.003.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01989092119038105
Inter Cos: 0.10477277636528015
Norm Quadratic Average: 27.59717559814453
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024674344807863235
Inter Cos: 0.10694743692874908
Norm Quadratic Average: 27.49095916748047
Nearest Class Center Accuracy: 0.35352

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029970597475767136
Inter Cos: 0.11059056222438812
Norm Quadratic Average: 26.524721145629883
Nearest Class Center Accuracy: 0.41784

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03297192230820656
Inter Cos: 0.09740231931209564
Norm Quadratic Average: 32.27596664428711
Nearest Class Center Accuracy: 0.472

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0341770276427269
Inter Cos: 0.08198758214712143
Norm Quadratic Average: 13.770278930664062
Nearest Class Center Accuracy: 0.57086

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06075619161128998
Inter Cos: 0.0883307084441185
Norm Quadratic Average: 5.081223011016846
Nearest Class Center Accuracy: 0.66688

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2483496516942978
Inter Cos: 0.32248684763908386
Norm Quadratic Average: 1.3616245985031128
Nearest Class Center Accuracy: 0.7955

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5694690942764282
Inter Cos: 0.45460987091064453
Norm Quadratic Average: 1.1171455383300781
Nearest Class Center Accuracy: 0.97198

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 3.553112506866455
Linear Weight Rank: 2624
Intra Cos: 0.7083333134651184
Inter Cos: 0.4146987795829773
Norm Quadratic Average: 8.258367538452148
Nearest Class Center Accuracy: 0.992

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.5691075325012207
Linear Weight Rank: 2904
Intra Cos: 0.7511500120162964
Inter Cos: 0.3546895980834961
Norm Quadratic Average: 9.788538932800293
Nearest Class Center Accuracy: 0.99792

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.5447237491607666
Linear Weight Rank: 9
Intra Cos: 0.7681705951690674
Inter Cos: 0.2649225890636444
Norm Quadratic Average: 11.493831634521484
Nearest Class Center Accuracy: 0.99936

Output Layer:
Intra Cos: 0.780566930770874
Inter Cos: 0.24271877110004425
Norm Quadratic Average: 15.440149307250977
Nearest Class Center Accuracy: 0.99982

Test Set:
Average Loss: 0.9344447516441345
Accuracy: 0.7822
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23234078288078308, Weights: 0.0635758563876152
NC2 Equiangle: Features: 0.29139734903971354, Weights: 0.15998669730292425
NC3 Self-Duality: 0.19132356345653534
NC4 NCC Mismatch: 0.058499999999999996

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: 27.550134658813477
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024327652528882027
Inter Cos: 0.10757297277450562
Norm Quadratic Average: 27.456737518310547
Nearest Class Center Accuracy: 0.3682

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029041195288300514
Inter Cos: 0.112326979637146
Norm Quadratic Average: 26.533252716064453
Nearest Class Center Accuracy: 0.4287

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03120529279112816
Inter Cos: 0.09898516535758972
Norm Quadratic Average: 32.31599044799805
Nearest Class Center Accuracy: 0.4765

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030729170888662338
Inter Cos: 0.08338399976491928
Norm Quadratic Average: 13.79654312133789
Nearest Class Center Accuracy: 0.5672

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05466270446777344
Inter Cos: 0.08896293491125107
Norm Quadratic Average: 5.086276054382324
Nearest Class Center Accuracy: 0.6432

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.21434997022151947
Inter Cos: 0.31732669472694397
Norm Quadratic Average: 1.3617488145828247
Nearest Class Center Accuracy: 0.7001

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.421731173992157
Inter Cos: 0.44560179114341736
Norm Quadratic Average: 1.1080193519592285
Nearest Class Center Accuracy: 0.7626

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 3.553112506866455
Linear Weight Rank: 2624
Intra Cos: 0.4778284430503845
Inter Cos: 0.41796135902404785
Norm Quadratic Average: 8.138575553894043
Nearest Class Center Accuracy: 0.771

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.5691075325012207
Linear Weight Rank: 2904
Intra Cos: 0.46080315113067627
Inter Cos: 0.3850763738155365
Norm Quadratic Average: 9.59367561340332
Nearest Class Center Accuracy: 0.7774

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.5447237491607666
Linear Weight Rank: 9
Intra Cos: 0.428550124168396
Inter Cos: 0.3339056074619293
Norm Quadratic Average: 11.215919494628906
Nearest Class Center Accuracy: 0.7777

Output Layer:
Intra Cos: 0.4042980968952179
Inter Cos: 0.304936021566391
Norm Quadratic Average: 15.013019561767578
Nearest Class Center Accuracy: 0.7754

