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@@ -14,29 +14,83 @@ IoU metric: bbox
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.001
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.010
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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  Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.011
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  ```
 
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  ## After training result
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  ```
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  IoU metric: bbox
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- Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.006
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- Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.018
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- Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.002
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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- Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.001
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- Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.006
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.048
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.102
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.115
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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- Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.001
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.118
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  ```
 
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  ## Config
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  - dataset: NIH
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  - original model: facebook/detr-resnet-50
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  - lr: 0.0001
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  - max_epochs: 20
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14
  Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000
15
  Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.000
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.001
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.001
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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  Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.001
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  ```
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+
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  ## After training result
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  ```
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  IoU metric: bbox
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+ Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.007
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+ Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.022
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+ Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.004
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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+ Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.003
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+ Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.007
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.048
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.112
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.132
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.003
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.136
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  ```
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+
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  ## Config
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  - dataset: NIH
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  - original model: facebook/detr-resnet-50
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  - lr: 0.0001
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  - max_epochs: 20
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+
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+ ## Logging
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+
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+ ### Training process
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+ ```
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+
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
57
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
71
+ ```
72
+
73
+ ### Validation process
74
+ ```
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+ {'validation_loss': tensor(5.5535, device='cuda:0'), 'validation_loss_ce': tensor(1.7749, device='cuda:0'), 'validation_loss_bbox': tensor(0.4228, device='cuda:0'), 'validation_loss_giou': tensor(0.8322, device='cuda:0'), 'validation_cardinality_error': tensor(24.1875, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
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+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
79
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
80
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
81
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
82
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
83
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
84
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
85
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
86
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
87
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
88
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
89
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
90
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
91
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
92
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
93
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
94
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
95
+ {'training_loss': tensor(1.5684, device='cuda:0'), 'train_loss_ce': tensor(0.3539, device='cuda:0'), 'train_loss_bbox': tensor(0.1131, device='cuda:0'), 'train_loss_giou': tensor(0.3245, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0878, device='cuda:0'), 'validation_loss_ce': tensor(0.4173, device='cuda:0'), 'validation_loss_bbox': tensor(0.1414, device='cuda:0'), 'validation_loss_giou': tensor(0.4817, device='cuda:0'), 'validation_cardinality_error': tensor(1.1068, device='cuda:0')}
96
+ ```