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metrics.log

@@ -1,98 +1,10 @@
-Subset ('m0',) accuracies 
-{'m1': 0.4762, 'm2': 0.4815, 'm3': 0.3886, 'm4': 0.3878}
-Mean subset ('m0',) accuracies : 0.433525
-Subset ('m1',) accuracies 
-{'m0': 0.3418, 'm2': 0.6677, 'm3': 0.5174, 'm4': 0.5323}
-Mean subset ('m1',) accuracies : 0.5147999999999999
-Subset ('m2',) accuracies 
-{'m0': 0.319, 'm1': 0.606, 'm3': 0.4926, 'm4': 0.4966}
-Mean subset ('m2',) accuracies : 0.47855
-Subset ('m3',) accuracies 
-{'m0': 0.3115, 'm1': 0.5722, 'm2': 0.5918, 'm4': 0.479}
-Mean subset ('m3',) accuracies : 0.488625
-Subset ('m4',) accuracies 
-{'m0': 0.2541, 'm1': 0.4497, 'm2': 0.4525, 'm3': 0.376}
-Mean subset ('m4',) accuracies : 0.38307499999999994
-Subset ('m0', 'm1') accuracies 
-{'m2': 0.7927, 'm3': 0.6348, 'm4': 0.6208}
-Mean subset ('m0', 'm1') accuracies : 0.6827666666666667
-Subset ('m0', 'm2') accuracies 
-{'m1': 0.7382, 'm3': 0.6179, 'm4': 0.5872}
-Mean subset ('m0', 'm2') accuracies : 0.6477666666666667
-Subset ('m0', 'm3') accuracies 
-{'m1': 0.7221, 'm2': 0.7415, 'm4': 0.5873}
-Mean subset ('m0', 'm3') accuracies : 0.6836333333333333
-Subset ('m0', 'm4') accuracies 
-{'m1': 0.628, 'm2': 0.6413, 'm3': 0.5239}
-Mean subset ('m0', 'm4') accuracies : 0.5977333333333333
-Subset ('m1', 'm2') accuracies 
-{'m0': 0.4046, 'm3': 0.701, 'm4': 0.6826}
-Mean subset ('m1', 'm2') accuracies : 0.5960666666666666
-Subset ('m1', 'm3') accuracies 
-{'m0': 0.4197, 'm2': 0.8389, 'm4': 0.6763}
-Mean subset ('m1', 'm3') accuracies : 0.6449666666666666
-Subset ('m1', 'm4') accuracies 
-{'m0': 0.3826, 'm2': 0.7881, 'm3': 0.6287}
-Mean subset ('m1', 'm4') accuracies : 0.5998
-Subset ('m2', 'm3') accuracies 
-{'m0': 0.4066, 'm1': 0.7942, 'm4': 0.6528}
-Mean subset ('m2', 'm3') accuracies : 0.6178666666666667
-Subset ('m2', 'm4') accuracies 
-{'m0': 0.3764, 'm1': 0.7329, 'm3': 0.6055}
-Mean subset ('m2', 'm4') accuracies : 0.5716
-Subset ('m3', 'm4') accuracies 
-{'m0': 0.3775, 'm1': 0.7203, 'm2': 0.7427}
-Mean subset ('m3', 'm4') accuracies : 0.6135
-Subset ('m0', 'm1', 'm2') accuracies 
-{'m3': 0.7569, 'm4': 0.702}
-Mean subset ('m0', 'm1', 'm2') accuracies : 0.7294499999999999
-Subset ('m0', 'm1', 'm3') accuracies 
-{'m2': 0.8905, 'm4': 0.7066}
-Mean subset ('m0', 'm1', 'm3') accuracies : 0.79855
-Subset ('m0', 'm1', 'm4') accuracies 
-{'m2': 0.8456, 'm3': 0.6995}
-Mean subset ('m0', 'm1', 'm4') accuracies : 0.7725500000000001
-Subset ('m0', 'm2', 'm3') accuracies 
-{'m1': 0.8563, 'm4': 0.6806}
-Mean subset ('m0', 'm2', 'm3') accuracies : 0.76845
-Subset ('m0', 'm2', 'm4') accuracies 
-{'m1': 0.8072, 'm3': 0.6835}
-Mean subset ('m0', 'm2', 'm4') accuracies : 0.74535
-Subset ('m0', 'm3', 'm4') accuracies 
-{'m1': 0.8006, 'm2': 0.8226}
-Mean subset ('m0', 'm3', 'm4') accuracies : 0.8116
-Subset ('m1', 'm2', 'm3') accuracies 
-{'m0': 0.4451, 'm4': 0.7384}
-Mean subset ('m1', 'm2', 'm3') accuracies : 0.59175
-Subset ('m1', 'm2', 'm4') accuracies 
-{'m0': 0.4168, 'm3': 0.7522}
-Mean subset ('m1', 'm2', 'm4') accuracies : 0.5845
-Subset ('m1', 'm3', 'm4') accuracies 
-{'m0': 0.429, 'm2': 0.8923}
-Mean subset ('m1', 'm3', 'm4') accuracies : 0.66065
-Subset ('m2', 'm3', 'm4') accuracies 
-{'m0': 0.4054, 'm1': 0.8544}
-Mean subset ('m2', 'm3', 'm4') accuracies : 0.6299
-Subset ('m0', 'm1', 'm2', 'm3') accuracies 
-{'m4': 0.7376}
-Mean subset ('m0', 'm1', 'm2', 'm3') accuracies : 0.7376
-Subset ('m0', 'm1', 'm2', 'm4') accuracies 
-{'m3': 0.7818}
-Mean subset ('m0', 'm1', 'm2', 'm4') accuracies : 0.7818
-Subset ('m0', 'm1', 'm3', 'm4') accuracies 
-{'m2': 0.9164}
-Mean subset ('m0', 'm1', 'm3', 'm4') accuracies : 0.9164
-Subset ('m0', 'm2', 'm3', 'm4') accuracies 
-{'m1': 0.896}
-Mean subset ('m0', 'm2', 'm3', 'm4') accuracies : 0.896
-Subset ('m1', 'm2', 'm3', 'm4') accuracies 
-{'m0': 0.4418}
-Mean subset ('m1', 'm2', 'm3', 'm4') accuracies : 0.4418
-Conditional accuracies for 0 modalities : 0.45971499999999993 +- 0.046442455253786916
-Conditional accuracies for 1 modalities : 0.62557 +- 0.03597073640861107
-Conditional accuracies for 2 modalities : 0.709275 +- 0.08105552495049304
-Conditional accuracies for 3 modalities : 0.7547200000000001 +- 0.17032076091892026
-Joint coherence : 0.00559999980032444
-Uploading MVTCAE model to asenella/mmnistMVTCAE_config1_ repo in HF hub...
-Creating mmnistMVTCAE_config1_ in the HF hub since it does not exist...
-Successfully created mmnistMVTCAE_config1_ in the HF hub!
+Start computing FID for modality m0
+The FD for modality m0 is 106.36369737476707
+Start computing FID for modality m1
+The FD for modality m1 is 43.0120659419149
+Start computing FID for modality m2
+The FD for modality m2 is 71.99052732125912
+Start computing FID for modality m3
+The FD for modality m3 is 110.63167832989902
+Start computing FID for modality m4
+The FD for modality m4 is 49.402452587399864