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\deeplab_351
Max Epochs     20
Model Type     DEEPLAB
Batch Size     8
Model Arguments     class_balancing False;mixup False;focal_loss False;ignore_classes #;chip_size 224
Learning Rate     
Backbone Model     RESNET50
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 2:38:19 PM
Learning Rate - slice(0.0001737800828749376, 0.001737800828749376, None)
epoch      training loss        validation loss      accuracy             Dice                 
0          1.791172981262207    1.791172981262207    0.08162932842969894  0.04760141298174858  
1          1.8746477365493774   1.8746477365493774   0.11479591578245163  0.16498850286006927  
2          6.339532375335693    6.339532375335693    0.13803412020206451  0.1686229556798935   
3          8.851752281188965    8.851752281188965    0.2528267204761505   0.16998179256916046  
4          1.2231676578521729   1.2231676578521729   0.7009327411651611   0.2336999922990799   
5          0.8924859762191772   0.8924859166145325   0.7606026530265808   0.24232041835784912  
6          0.8320154547691345   0.8320154547691345   0.7889528870582581   0.277103990316391    
7          0.7650888562202454   0.7650888562202454   0.771806538105011    0.25677791237831116  
8          0.7882922887802124   0.7882922291755676   0.7251541018486023   0.11104923486709595  
9          0.7085747122764587   0.7085747122764587   0.7305152416229248   0.10194819420576096  
10         0.6303458213806152   0.6303458213806152   0.7794197201728821   0.3011516034603119   
11         0.6448149681091309   0.6448149681091309   0.7740022540092468   0.2915407717227936   
12         0.6086469888687134   0.6086469888687134   0.7821136116981506   0.31960728764533997  
13         0.6170032024383545   0.6170032024383545   0.7810041904449463   0.3322853744029999   
14         0.5880154967308044   0.5880154967308044   0.790361225605011    0.3341427147388458   
15         0.5670560002326965   0.5670560002326965   0.789524257183075    0.31823912262916565  
16         0.5626857280731201   0.5626857280731201   0.7902582287788391   0.31893765926361084  
17         0.5623242855072021   0.5623242855072021   0.7908394932746887   0.32146909832954407  
18         0.5593257546424866   0.5593257546424866   0.7915968894958496   0.3254910409450531   
19         0.5630885362625122   0.5630885362625122   0.7906602025032043   0.32840314507484436  
{'accuracy': '7.9160e-01'}
             NoData  Bare Land  Trees  Buildings1      Road  Parks
precision  0.810488   0.763762    0.0    0.539077  0.434826    0.0
recall     0.932186   0.839775    0.0    0.029109  0.496244    0.0
f1         0.867087   0.799967    0.0    0.055235  0.463509    0.0
Succeeded at Friday, October 22, 2021 3:31:37 PM (Elapsed Time: 53 minutes 17 seconds)