Train Deep Learning Model ===================== Parameters Input Training Data E:\Akshay_Phd\Spatial data\Satellite images of J,M,V\Jaipur\Arc_Pro\RGB3_351_class\deep_learning_2210_update Output Model E:\Akshay_Phd\Spatial data\Satellite images of J,M,V\Jaipur\Arc_Pro\RGB3_351_class\deep_learning_351_2210_update Max Epochs 30 Model Type UNET Batch Size 8 Model Arguments class_balancing False;mixup False;focal_loss False;ignore_classes #;chip_size 224 Learning Rate Backbone Model RESNET34 Pre-trained Model Validation % 10 Stop when model stops improving STOP_TRAINING Output Model Freeze Model FREEZE_MODEL ===================== Messages Start Time: Friday, October 22, 2021 12:39:08 PM Learning Rate - slice(1.0964781961431852e-05, 0.00010964781961431851, None) epoch training loss validation loss accuracy Dice 0 1.9159733057022095 1.9159733057022095 0.4097842276096344 0.001209718408063054 1 1.4877467155456543 1.4877467155456543 0.5826656818389893 0.00035535372444428504 2 1.2731207609176636 1.2731207609176636 0.7026832103729248 0.00020585833408404142 3 1.0821261405944824 1.0821261405944824 0.695730984210968 0.01059943437576294 4 0.9224348068237305 0.9224348068237305 0.7237690091133118 0.04734618961811066 5 0.8667362928390503 0.8667362332344055 0.7442269921302795 0.2071378380060196 6 0.8039462566375732 0.8039462566375732 0.7763804793357849 0.2122984081506729 7 0.7370654344558716 0.7370654940605164 0.773623526096344 0.2937856614589691 8 0.7496110796928406 0.7496110796928406 0.7900622487068176 0.3955630362033844 9 0.7306728959083557 0.7306728959083557 0.7662162780761719 0.23153400421142578 10 0.6459059715270996 0.6459059715270996 0.8011533617973328 0.4448840618133545 11 0.6585891842842102 0.6585891842842102 0.7760151028633118 0.2718440592288971 12 0.6122271418571472 0.6122271418571472 0.8003062605857849 0.3634450137615204 13 0.6911121606826782 0.691112220287323 0.7679833769798279 0.3856322467327118 14 0.6803950071334839 0.6803949475288391 0.7466949820518494 0.24173887073993683 15 0.6131340861320496 0.6131340861320496 0.7970311045646667 0.4516953229904175 16 0.5920544862747192 0.5920544862747192 0.7997581958770752 0.38619399070739746 17 0.5813532471656799 0.5813532471656799 0.8040663599967957 0.4540465176105499 18 0.5812987089157104 0.5812987089157104 0.801495373249054 0.4610978066921234 19 0.5634425282478333 0.5634425282478333 0.8044283986091614 0.44098028540611267 20 0.5530598163604736 0.5530598163604736 0.8016182780265808 0.48239102959632874 21 0.5466501712799072 0.5466501712799072 0.8054912686347961 0.42608606815338135 22 0.5530131459236145 0.5530131459236145 0.803780734539032 0.47437265515327454 23 0.5490578413009644 0.5490578413009644 0.8022229075431824 0.47614479064941406 24 0.5565797686576843 0.5565797686576843 0.7996087074279785 0.4500833749771118 25 0.550960123538971 0.550960123538971 0.8030068278312683 0.46155276894569397 26 0.5529464483261108 0.5529464483261108 0.8027011752128601 0.47714900970458984 27 0.5496675372123718 0.5496675372123718 0.8025550246238708 0.4732299745082855 {'accuracy': '8.0549e-01'} NoData Bare Land Trees Buildings1 Road Parks precision 0.818530 0.788081 0.026882 0.595818 0.560559 0.769452 recall 0.937217 0.782633 0.000922 0.276467 0.123264 0.073716 f1 0.873862 0.785347 0.001783 0.377684 0.202090 0.134543 Succeeded at Friday, October 22, 2021 1:19:33 PM (Elapsed Time: 40 minutes 24 seconds)