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results.txt
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Tuning 30 epochs
Micro
model metrics/precision(B) metrics/recall(B) metrics/mAP50(B) metrics/mAP50-95(B)
n 0.0406667 0.83945 0.312089 0.0968644
s 0.411868 0.56422 0.410304 0.144141
l 0.387779 0.33945 0.260499 0.0770244
m 0.40572 0.645132 0.443174 0.168049
x 0.492631 0.534474 0.477487 0.125968
Training 50 epochs
Micro
n train1 {'metrics/precision(B)': 0.5414162308013722, 'metrics/recall(B)': 0.47706422018348627, 'metrics/mAP50(B)': 0.4651260164006293, 'metrics/mAP50-95(B)': 0.15814004479113142, 'fitness': 0.18883864195208122}
s train2 {'metrics/precision(B)': 0.6264528662424486, 'metrics/recall(B)': 0.518348623853211, 'metrics/mAP50(B)': 0.5385276597059194, 'metrics/mAP50-95(B)': 0.19026044875301723, 'fitness': 0.22508716984830746}
l train3 {'metrics/precision(B)': 0.44397393479543373, 'metrics/recall(B)': 0.43119266055045874, 'metrics/mAP50(B)': 0.3121359448785275, 'metrics/mAP50-95(B)': 0.09143586934295116, 'fitness': 0.1135058768965088}
m train4 {'metrics/precision(B)': 0.3827781417251571, 'metrics/recall(B)': 0.5275229357798165, 'metrics/mAP50(B)': 0.3451034012527603, 'metrics/mAP50-95(B)': 0.10237087965372293, 'fitness': 0.1266441318136267}
x train5 {'metrics/precision(B)': 0.3827781417251571, 'metrics/recall(B)': 0.5275229357798165, 'metrics/mAP50(B)': 0.3451034012527603, 'metrics/mAP50-95(B)': 0.10237087965372293, 'fitness': 0.1266441318136267}
ren train11 {'metrics/precision(B)': 0.6902122553532517, 'metrics/recall(B)': 0.7339449541284404, 'metrics/mAP50(B)': 0.6978231866221873, 'metrics/mAP50-95(B)': 0.2768027388514156, 'fitness': 0.3189047836284928}
res train12 {'metrics/precision(B)': 0.5874216054582164, 'metrics/recall(B)': 0.7247706422018348, 'metrics/mAP50(B)': 0.6673627876202782, 'metrics/mAP50-95(B)': 0.2716520410746606, 'fitness': 0.3112231157292224}
rel train13 {'metrics/precision(B)': 0.6320874479880857, 'metrics/recall(B)': 0.555045871559633, 'metrics/mAP50(B)': 0.5902226358236523, 'metrics/mAP50-95(B)': 0.24912735332724653, 'fitness': 0.2832368815768871}
rem train14 {'metrics/precision(B)': 0.6573764482274, 'metrics/recall(B)': 0.6651376146788991, 'metrics/mAP50(B)': 0.6482527443794568, 'metrics/mAP50-95(B)': 0.24832120980556388, 'fitness': 0.2883143632629532}
rex train15 {'metrics/precision(B)': 0.6645329065873431, 'metrics/recall(B)': 0.6972477064220184, 'metrics/mAP50(B)': 0.6639770173033037, 'metrics/mAP50-95(B)': 0.25329698361319336, 'fitness': 0.2943649869822044}
Fitness Values:
n
s
l
m
x
ren
res 0.3189047836284928
rel
rem
rex
Detect Metrics:
n val3 5035007 {'metrics/precision(B)': 0.5414162308013722, 'metrics/recall(B)': 0.47706422018348627, 'metrics/mAP50(B)': 0.4651260164006293, 'metrics/mAP50-95(B)': 0.15814004479113142, 'fitness': 0.18883864195208122}
s val4 5035012 {'metrics/precision(B)': 0.6218039110951126, 'metrics/recall(B)': 0.518348623853211, 'metrics/mAP50(B)': 0.5380402847015369, 'metrics/mAP50-95(B)': 0.19034453442560192, 'fitness': 0.22511410945319543}
l val5 5035093 {'metrics/precision(B)': 0.44397393479543373, 'metrics/recall(B)': 0.43119266055045874, 'metrics/mAP50(B)': 0.3121359448785275, 'metrics/mAP50-95(B)': 0.09143586934295116, 'fitness': 0.1135058768965088}
m val6 5035174 {'metrics/precision(B)': 0.5037817648197777, 'metrics/recall(B)': 0.6284403669724771, 'metrics/mAP50(B)': 0.5220074218283881, 'metrics/mAP50-95(B)': 0.16934166928818686, 'fitness': 0.204608244542207}
x val7 5035175 {'metrics/precision(B)': 0.3827781417251571, 'metrics/recall(B)': 0.5275229357798165, 'metrics/mAP50(B)': 0.3451034012527603, 'metrics/mAP50-95(B)': 0.10237087965372293, 'fitness': 0.1266441318136267}
ren val8 5035177 {'metrics/precision(B)': 0.6902122553532517, 'metrics/recall(B)': 0.7339449541284404, 'metrics/mAP50(B)': 0.6978231866221873, 'metrics/mAP50-95(B)': 0.2768027388514156, 'fitness': 0.3189047836284928}
res val9 5035179 {'metrics/precision(B)': 0.5874216054582164, 'metrics/recall(B)': 0.7247706422018348, 'metrics/mAP50(B)': 0.6673627876202782, 'metrics/mAP50-95(B)': 0.2716520410746606, 'fitness': 0.3112231157292224}
rel val10 5035181 {'metrics/precision(B)': 0.6320874479880857, 'metrics/recall(B)': 0.555045871559633, 'metrics/mAP50(B)': 0.5902226358236523, 'metrics/mAP50-95(B)': 0.24912735332724653, 'fitness': 0.2832368815768871}
rem val11 5035182 {'metrics/precision(B)': 0.6573764482274, 'metrics/recall(B)': 0.6651376146788991, 'metrics/mAP50(B)': 0.6482527443794568, 'metrics/mAP50-95(B)': 0.24832120980556388, 'fitness': 0.2883143632629532}
rex val12 5035186 {'metrics/precision(B)': 0.6645329065873431, 'metrics/recall(B)': 0.6972477064220184, 'metrics/mAP50(B)': 0.6639770173033037, 'metrics/mAP50-95(B)': 0.25329698361319336, 'fitness': 0.2943649869822044}
Fitness Values:
n 0.18883864195208122
s 0.22511410945319543
l 0.1135058768965088
m 0.204608244542207
x 0.1266441318136267
ren 0.3189047836284928
res 0.3112231157292224
rel 0.2832368815768871
rem 0.2883143632629532
rex 0.2943649869822044