Upload metrics.log

metrics.log

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+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!