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Create metrics.log

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  1. metrics.log +155 -0
metrics.log ADDED
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+ Subset ['m0'] accuracies
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+ {'m1': 0.6354, 'm2': 0.592, 'm3': 0.6089, 'm4': 0.4787}
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+ Mean subset ['m0'] accuracies : 0.57875
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+ Subset ['m1'] accuracies
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+ {'m0': 0.5028, 'm2': 0.6489, 'm3': 0.6556, 'm4': 0.5353}
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+ Mean subset ['m1'] accuracies : 0.58565
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+ Subset ['m2'] accuracies
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+ {'m0': 0.4902, 'm1': 0.6807, 'm3': 0.6379, 'm4': 0.5249}
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+ Mean subset ['m2'] accuracies : 0.5834250000000001
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+ Subset ['m3'] accuracies
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+ {'m0': 0.5151, 'm1': 0.7395, 'm2': 0.6902, 'm4': 0.5657}
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+ Mean subset ['m3'] accuracies : 0.627625
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+ Subset ['m4'] accuracies
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+ {'m0': 0.4535, 'm1': 0.6194, 'm2': 0.5888, 'm3': 0.5973}
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+ Mean subset ['m4'] accuracies : 0.56475
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+ Subset ['m0', 'm1'] accuracies
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+ {'m2': 0.7575, 'm3': 0.797, 'm4': 0.6147}
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+ Mean subset ['m0', 'm1'] accuracies : 0.7230666666666666
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+ Subset ['m0', 'm2'] accuracies
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+ {'m1': 0.7961, 'm3': 0.7815, 'm4': 0.6085}
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+ Mean subset ['m0', 'm2'] accuracies : 0.7286999999999999
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+ Subset ['m0', 'm3'] accuracies
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+ {'m1': 0.8437, 'm2': 0.7746, 'm4': 0.618}
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+ Mean subset ['m0', 'm3'] accuracies : 0.7454333333333333
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+ Subset ['m0', 'm4'] accuracies
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+ {'m1': 0.787, 'm2': 0.7183, 'm3': 0.7723}
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+ Mean subset ['m0', 'm4'] accuracies : 0.7592
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+ Subset ['m1', 'm2'] accuracies
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+ {'m0': 0.5982, 'm3': 0.8002, 'm4': 0.6311}
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+ Mean subset ['m1', 'm2'] accuracies : 0.6765
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+ Subset ['m1', 'm3'] accuracies
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+ {'m0': 0.61, 'm2': 0.7933, 'm4': 0.642}
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+ Mean subset ['m1', 'm3'] accuracies : 0.6817666666666667
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+ Subset ['m1', 'm4'] accuracies
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+ {'m0': 0.5827, 'm2': 0.7571, 'm3': 0.7969}
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+ Mean subset ['m1', 'm4'] accuracies : 0.7122333333333333
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+ Subset ['m2', 'm3'] accuracies
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+ {'m0': 0.6135, 'm1': 0.8535, 'm4': 0.6411}
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+ Mean subset ['m2', 'm3'] accuracies : 0.7027000000000001
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+ Subset ['m2', 'm4'] accuracies
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+ {'m0': 0.5865, 'm1': 0.7976, 'm3': 0.7838}
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+ Mean subset ['m2', 'm4'] accuracies : 0.7226333333333335
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+ Subset ['m3', 'm4'] accuracies
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+ {'m0': 0.5963, 'm1': 0.8431, 'm2': 0.7831}
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+ Mean subset ['m3', 'm4'] accuracies : 0.7408333333333333
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+ Subset ['m0', 'm1', 'm2'] accuracies
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+ {'m3': 0.884, 'm4': 0.6554}
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+ Mean subset ['m0', 'm1', 'm2'] accuracies : 0.7697
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+ Subset ['m0', 'm1', 'm3'] accuracies
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+ {'m2': 0.8448, 'm4': 0.6528}
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+ Mean subset ['m0', 'm1', 'm3'] accuracies : 0.7488
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+ Subset ['m0', 'm1', 'm4'] accuracies
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+ {'m2': 0.8262, 'm3': 0.8799}
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+ Mean subset ['m0', 'm1', 'm4'] accuracies : 0.8530500000000001
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+ Subset ['m0', 'm2', 'm3'] accuracies
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+ {'m1': 0.9102, 'm4': 0.6506}
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+ Mean subset ['m0', 'm2', 'm3'] accuracies : 0.7804
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+ Subset ['m0'] accuracies
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+ {'m1': 0.634, 'm2': 0.589, 'm3': 0.6064, 'm4': 0.4893}
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+ Mean subset ['m0'] accuracies : 0.5796749999999999
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+ Subset ['m1'] accuracies
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+ {'m0': 0.4946, 'm2': 0.6424, 'm3': 0.6501, 'm4': 0.5433}
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+ Mean subset ['m1'] accuracies : 0.5826
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+ Subset ['m2'] accuracies
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+ {'m0': 0.4796, 'm1': 0.6785, 'm3': 0.6294, 'm4': 0.5215}
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+ Mean subset ['m2'] accuracies : 0.57725
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+ Subset ['m3'] accuracies
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+ {'m0': 0.5166, 'm1': 0.7344, 'm2': 0.68, 'm4': 0.5639}
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+ Mean subset ['m3'] accuracies : 0.623725
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+ Subset ['m4'] accuracies
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+ {'m0': 0.4515, 'm1': 0.6235, 'm2': 0.5899, 'm3': 0.602}
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+ Mean subset ['m4'] accuracies : 0.566725
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+ Subset ['m0', 'm1'] accuracies
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+ {'m2': 0.7512, 'm3': 0.794, 'm4': 0.618}
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+ Mean subset ['m0', 'm1'] accuracies : 0.7210666666666666
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+ Subset ['m0', 'm2'] accuracies
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+ {'m1': 0.7975, 'm3': 0.7821, 'm4': 0.6162}
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+ Mean subset ['m0', 'm2'] accuracies : 0.7319333333333334
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+ Subset ['m0', 'm3'] accuracies
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+ {'m1': 0.8415, 'm2': 0.7741, 'm4': 0.6172}
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+ Mean subset ['m0', 'm3'] accuracies : 0.7442666666666667
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+ Subset ['m0', 'm4'] accuracies
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+ {'m1': 0.7785, 'm2': 0.7208, 'm3': 0.7635}
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+ Mean subset ['m0', 'm4'] accuracies : 0.7542666666666666
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+ Subset ['m1', 'm2'] accuracies
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+ {'m0': 0.6056, 'm3': 0.8028, 'm4': 0.636}
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+ Mean subset ['m1', 'm2'] accuracies : 0.6814666666666667
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+ Subset ['m1', 'm3'] accuracies
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+ {'m0': 0.616, 'm2': 0.7975, 'm4': 0.6367}
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+ Mean subset ['m1', 'm3'] accuracies : 0.6834000000000001
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+ Subset ['m1', 'm4'] accuracies
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+ {'m0': 0.5796, 'm2': 0.7538, 'm3': 0.7965}
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+ Mean subset ['m1', 'm4'] accuracies : 0.7099666666666667
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+ Subset ['m2', 'm3'] accuracies
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+ {'m0': 0.6101, 'm1': 0.842, 'm4': 0.6407}
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+ Mean subset ['m2', 'm3'] accuracies : 0.6976
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+ Subset ['m2', 'm4'] accuracies
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+ {'m0': 0.5831, 'm1': 0.7914, 'm3': 0.7776}
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+ Mean subset ['m2', 'm4'] accuracies : 0.7173666666666666
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+ Subset ['m3', 'm4'] accuracies
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+ {'m0': 0.5932, 'm1': 0.8385, 'm2': 0.7796}
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+ Mean subset ['m3', 'm4'] accuracies : 0.7371
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+ Subset ['m0', 'm1', 'm2'] accuracies
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+ {'m3': 0.8873, 'm4': 0.6525}
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+ Mean subset ['m0', 'm1', 'm2'] accuracies : 0.7699
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+ Subset ['m0', 'm1', 'm3'] accuracies
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+ {'m2': 0.8437, 'm4': 0.6521}
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+ Mean subset ['m0', 'm1', 'm3'] accuracies : 0.7479
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+ Subset ['m0', 'm1', 'm4'] accuracies
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+ {'m2': 0.8179, 'm3': 0.8803}
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+ Mean subset ['m0', 'm1', 'm4'] accuracies : 0.8491
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+ Subset ['m0', 'm2', 'm3'] accuracies
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+ {'m1': 0.9097, 'm4': 0.6601}
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+ Mean subset ['m0', 'm2', 'm3'] accuracies : 0.7848999999999999
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+ Subset ['m0', 'm2', 'm4'] accuracies
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+ {'m1': 0.8857, 'm3': 0.8755}
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+ Mean subset ['m0', 'm2', 'm4'] accuracies : 0.8806
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+ Subset ['m0', 'm3', 'm4'] accuracies
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+ {'m1': 0.9037, 'm2': 0.8349}
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+ Mean subset ['m0', 'm3', 'm4'] accuracies : 0.8693
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+ Subset ['m1', 'm2', 'm3'] accuracies
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+ {'m0': 0.6507, 'm4': 0.6671}
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+ Mean subset ['m1', 'm2', 'm3'] accuracies : 0.6589
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+ Subset ['m1', 'm2', 'm4'] accuracies
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+ {'m0': 0.6391, 'm3': 0.8868}
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+ Mean subset ['m1', 'm2', 'm4'] accuracies : 0.76295
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+ Subset ['m1', 'm3', 'm4'] accuracies
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+ {'m0': 0.6433, 'm2': 0.8492}
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+ Mean subset ['m1', 'm3', 'm4'] accuracies : 0.74625
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+ Subset ['m2', 'm3', 'm4'] accuracies
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+ {'m0': 0.6368, 'm1': 0.9056}
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+ Mean subset ['m2', 'm3', 'm4'] accuracies : 0.7712
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+ Subset ['m0', 'm1', 'm2', 'm3'] accuracies
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+ {'m4': 0.6559}
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+ Mean subset ['m0', 'm1', 'm2', 'm3'] accuracies : 0.6559
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+ Subset ['m0', 'm1', 'm2', 'm4'] accuracies
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+ {'m3': 0.9293}
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+ Mean subset ['m0', 'm1', 'm2', 'm4'] accuracies : 0.9293
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+ Subset ['m0', 'm1', 'm3', 'm4'] accuracies
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+ {'m2': 0.8774}
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+ Mean subset ['m0', 'm1', 'm3', 'm4'] accuracies : 0.8774
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+ Subset ['m0', 'm2', 'm3', 'm4'] accuracies
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+ {'m1': 0.9395}
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+ Mean subset ['m0', 'm2', 'm3', 'm4'] accuracies : 0.9395
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+ Subset ['m1', 'm2', 'm3', 'm4'] accuracies
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+ {'m0': 0.653}
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+ Mean subset ['m1', 'm2', 'm3', 'm4'] accuracies : 0.653
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+ Conditional accuracies for 1 modalities : 0.5859949999999999 +- 0.01961035058330165
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+ Conditional accuracies for 2 modalities : 0.7178433333333334 +- 0.023635261087338683
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+ Conditional accuracies for 3 modalities : 0.7841 +- 0.06326958590033602
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+ Conditional accuracies for 4 modalities : 0.8110199999999999 +- 0.12956551084297085
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+ Joint coherence : 0.03179999813437462
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+ Uploading JNF model to asenella/mmnistJNF_config2_ repo in HF hub...
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+ Creating mmnistJNF_config2_ in the HF hub since it does not exist...
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+ Successfully created mmnistJNF_config2_ in the HF hub!