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README.md
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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 ] = 0.000
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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.
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.
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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.
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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.
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.
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Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.
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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.
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Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.
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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.
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Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.
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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: 50
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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 ] = 0.000
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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 ] = 0.002
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.002
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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 ] = 0.002
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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 ] = 0.015
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.035
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Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.010
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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 ] = 0.009
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Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.018
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.080
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.183
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.201
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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 ] = 0.016
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Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.225
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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: 50
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## Logging
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### Training process
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```
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{'validation_loss': tensor(6.3440, device='cuda:0'), 'validation_loss_ce': tensor(2.0978, device='cuda:0'), 'validation_loss_bbox': tensor(0.4936, device='cuda:0'), 'validation_loss_giou': tensor(0.8890, device='cuda:0'), 'validation_cardinality_error': tensor(85.6562, device='cuda:0')}
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{'training_loss': tensor(3.1706, device='cuda:0'), 'train_loss_ce': tensor(0.5251, device='cuda:0'), 'train_loss_bbox': tensor(0.2706, device='cuda:0'), 'train_loss_giou': tensor(0.6462, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.9125, device='cuda:0'), 'validation_loss_ce': tensor(0.5056, device='cuda:0'), 'validation_loss_bbox': tensor(0.2312, device='cuda:0'), 'validation_loss_giou': tensor(0.6255, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.4987, device='cuda:0'), 'train_loss_ce': tensor(0.5532, device='cuda:0'), 'train_loss_bbox': tensor(0.1583, device='cuda:0'), 'train_loss_giou': tensor(0.5770, device='cuda:0'), 'train_cardinality_error': tensor(1.3125, device='cuda:0'), 'validation_loss': tensor(2.3335, device='cuda:0'), 'validation_loss_ce': tensor(0.4910, device='cuda:0'), 'validation_loss_bbox': tensor(0.1606, device='cuda:0'), 'validation_loss_giou': tensor(0.5197, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.5471, device='cuda:0'), 'train_loss_ce': tensor(0.4087, device='cuda:0'), 'train_loss_bbox': tensor(0.1558, device='cuda:0'), 'train_loss_giou': tensor(0.6798, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3420, device='cuda:0'), 'validation_loss_ce': tensor(0.4825, device='cuda:0'), 'validation_loss_bbox': tensor(0.1571, device='cuda:0'), 'validation_loss_giou': tensor(0.5370, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.4962, device='cuda:0'), 'train_loss_ce': tensor(0.5160, device='cuda:0'), 'train_loss_bbox': tensor(0.1702, device='cuda:0'), 'train_loss_giou': tensor(0.5646, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.4121, device='cuda:0'), 'validation_loss_ce': tensor(0.4837, device='cuda:0'), 'validation_loss_bbox': tensor(0.1671, device='cuda:0'), 'validation_loss_giou': tensor(0.5463, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.0146, device='cuda:0'), 'train_loss_ce': tensor(0.4475, device='cuda:0'), 'train_loss_bbox': tensor(0.1417, device='cuda:0'), 'train_loss_giou': tensor(0.4294, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.4437, device='cuda:0'), 'validation_loss_ce': tensor(0.4664, device='cuda:0'), 'validation_loss_bbox': tensor(0.1689, device='cuda:0'), 'validation_loss_giou': tensor(0.5664, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.5258, device='cuda:0'), 'train_loss_ce': tensor(0.4352, device='cuda:0'), 'train_loss_bbox': tensor(0.1822, device='cuda:0'), 'train_loss_giou': tensor(0.5898, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2827, device='cuda:0'), 'validation_loss_ce': tensor(0.4655, device='cuda:0'), 'validation_loss_bbox': tensor(0.1534, device='cuda:0'), 'validation_loss_giou': tensor(0.5252, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.5122, device='cuda:0'), 'train_loss_ce': tensor(0.4750, device='cuda:0'), 'train_loss_bbox': tensor(0.1781, device='cuda:0'), 'train_loss_giou': tensor(0.5734, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.3420, device='cuda:0'), 'validation_loss_ce': tensor(0.4609, device='cuda:0'), 'validation_loss_bbox': tensor(0.1545, device='cuda:0'), 'validation_loss_giou': tensor(0.5543, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.5104, device='cuda:0'), 'train_loss_ce': tensor(0.4122, device='cuda:0'), 'train_loss_bbox': tensor(0.1681, device='cuda:0'), 'train_loss_giou': tensor(0.6288, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2988, device='cuda:0'), 'validation_loss_ce': tensor(0.4562, device='cuda:0'), 'validation_loss_bbox': tensor(0.1513, device='cuda:0'), 'validation_loss_giou': tensor(0.5432, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.5571, device='cuda:0'), 'train_loss_ce': tensor(0.5181, device='cuda:0'), 'train_loss_bbox': tensor(0.1580, device='cuda:0'), 'train_loss_giou': tensor(0.6245, device='cuda:0'), 'train_cardinality_error': tensor(1.3125, device='cuda:0'), 'validation_loss': tensor(2.3666, device='cuda:0'), 'validation_loss_ce': tensor(0.4579, device='cuda:0'), 'validation_loss_bbox': tensor(0.1604, device='cuda:0'), 'validation_loss_giou': tensor(0.5533, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.1376, device='cuda:0'), 'train_loss_ce': tensor(0.5280, device='cuda:0'), 'train_loss_bbox': tensor(0.1437, device='cuda:0'), 'train_loss_giou': tensor(0.4456, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.2616, device='cuda:0'), 'validation_loss_ce': tensor(0.4543, device='cuda:0'), 'validation_loss_bbox': tensor(0.1543, device='cuda:0'), 'validation_loss_giou': tensor(0.5179, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.2242, device='cuda:0'), 'train_loss_ce': tensor(0.4644, device='cuda:0'), 'train_loss_bbox': tensor(0.1293, device='cuda:0'), 'train_loss_giou': tensor(0.5567, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.2209, device='cuda:0'), 'validation_loss_ce': tensor(0.4515, device='cuda:0'), 'validation_loss_bbox': tensor(0.1492, device='cuda:0'), 'validation_loss_giou': tensor(0.5117, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.1088, device='cuda:0'), 'train_loss_ce': tensor(0.3916, device='cuda:0'), 'train_loss_bbox': tensor(0.1388, device='cuda:0'), 'train_loss_giou': tensor(0.5116, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.1887, device='cuda:0'), 'validation_loss_ce': tensor(0.4398, device='cuda:0'), 'validation_loss_bbox': tensor(0.1450, device='cuda:0'), 'validation_loss_giou': tensor(0.5119, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.1986, device='cuda:0'), 'train_loss_ce': tensor(0.4151, device='cuda:0'), 'train_loss_bbox': tensor(0.1447, device='cuda:0'), 'train_loss_giou': tensor(0.5301, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.1999, device='cuda:0'), 'validation_loss_ce': tensor(0.4299, device='cuda:0'), 'validation_loss_bbox': tensor(0.1486, device='cuda:0'), 'validation_loss_giou': tensor(0.5135, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.0995, device='cuda:0'), 'train_loss_ce': tensor(0.4170, device='cuda:0'), 'train_loss_bbox': tensor(0.1438, device='cuda:0'), 'train_loss_giou': tensor(0.4818, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.1373, device='cuda:0'), 'validation_loss_ce': tensor(0.4293, device='cuda:0'), 'validation_loss_bbox': tensor(0.1426, device='cuda:0'), 'validation_loss_giou': tensor(0.4974, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.2508, device='cuda:0'), 'train_loss_ce': tensor(0.4002, device='cuda:0'), 'train_loss_bbox': tensor(0.1417, device='cuda:0'), 'train_loss_giou': tensor(0.5711, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.1380, device='cuda:0'), 'validation_loss_ce': tensor(0.4244, device='cuda:0'), 'validation_loss_bbox': tensor(0.1417, device='cuda:0'), 'validation_loss_giou': tensor(0.5025, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.3045, device='cuda:0'), 'train_loss_ce': tensor(0.4336, device='cuda:0'), 'train_loss_bbox': tensor(0.1572, device='cuda:0'), 'train_loss_giou': tensor(0.5425, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.1376, device='cuda:0'), 'validation_loss_ce': tensor(0.4275, device='cuda:0'), 'validation_loss_bbox': tensor(0.1441, device='cuda:0'), 'validation_loss_giou': tensor(0.4948, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.0827, device='cuda:0'), 'train_loss_ce': tensor(0.4346, device='cuda:0'), 'train_loss_bbox': tensor(0.1247, device='cuda:0'), 'train_loss_giou': tensor(0.5122, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.0851, device='cuda:0'), 'validation_loss_ce': tensor(0.4186, device='cuda:0'), 'validation_loss_bbox': tensor(0.1376, device='cuda:0'), 'validation_loss_giou': tensor(0.4894, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.2029, device='cuda:0'), 'train_loss_ce': tensor(0.4592, device='cuda:0'), 'train_loss_bbox': tensor(0.1341, device='cuda:0'), 'train_loss_giou': tensor(0.5367, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.0779, device='cuda:0'), 'validation_loss_ce': tensor(0.4182, device='cuda:0'), 'validation_loss_bbox': tensor(0.1365, device='cuda:0'), 'validation_loss_giou': tensor(0.4885, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.3557, device='cuda:0'), 'train_loss_ce': tensor(0.5089, device='cuda:0'), 'train_loss_bbox': tensor(0.1324, device='cuda:0'), 'train_loss_giou': tensor(0.5923, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.1129, device='cuda:0'), 'validation_loss_ce': tensor(0.4233, device='cuda:0'), 'validation_loss_bbox': tensor(0.1375, device='cuda:0'), 'validation_loss_giou': tensor(0.5011, device='cuda:0'), 'validation_cardinality_error': tensor(1.0409, device='cuda:0')}
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{'training_loss': tensor(1.9955, device='cuda:0'), 'train_loss_ce': tensor(0.4479, device='cuda:0'), 'train_loss_bbox': tensor(0.1117, device='cuda:0'), 'train_loss_giou': tensor(0.4946, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.0669, device='cuda:0'), 'validation_loss_ce': tensor(0.4158, device='cuda:0'), 'validation_loss_bbox': tensor(0.1365, device='cuda:0'), 'validation_loss_giou': tensor(0.4842, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.1262, device='cuda:0'), 'train_loss_ce': tensor(0.4115, device='cuda:0'), 'train_loss_bbox': tensor(0.1496, device='cuda:0'), 'train_loss_giou': tensor(0.4833, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.0470, device='cuda:0'), 'validation_loss_ce': tensor(0.4140, device='cuda:0'), 'validation_loss_bbox': tensor(0.1342, device='cuda:0'), 'validation_loss_giou': tensor(0.4809, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.1451, device='cuda:0'), 'train_loss_ce': tensor(0.4341, device='cuda:0'), 'train_loss_bbox': tensor(0.1283, device='cuda:0'), 'train_loss_giou': tensor(0.5347, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.0579, device='cuda:0'), 'validation_loss_ce': tensor(0.4170, device='cuda:0'), 'validation_loss_bbox': tensor(0.1333, device='cuda:0'), 'validation_loss_giou': tensor(0.4873, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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{'training_loss': tensor(2.1771, device='cuda:0'), 'train_loss_ce': tensor(0.4315, device='cuda:0'), 'train_loss_bbox': tensor(0.1587, device='cuda:0'), 'train_loss_giou': tensor(0.4760, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.0670, device='cuda:0'), 'validation_loss_ce': tensor(0.4111, device='cuda:0'), 'validation_loss_bbox': tensor(0.1353, device='cuda:0'), 'validation_loss_giou': tensor(0.4896, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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| 73 |
+
{'training_loss': tensor(1.9001, device='cuda:0'), 'train_loss_ce': tensor(0.3586, device='cuda:0'), 'train_loss_bbox': tensor(0.1362, device='cuda:0'), 'train_loss_giou': tensor(0.4302, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0867, device='cuda:0'), 'validation_loss_ce': tensor(0.4068, device='cuda:0'), 'validation_loss_bbox': tensor(0.1386, device='cuda:0'), 'validation_loss_giou': tensor(0.4934, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
|
| 74 |
+
{'training_loss': tensor(2.2456, device='cuda:0'), 'train_loss_ce': tensor(0.4781, device='cuda:0'), 'train_loss_bbox': tensor(0.1459, device='cuda:0'), 'train_loss_giou': tensor(0.5189, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.0596, device='cuda:0'), 'validation_loss_ce': tensor(0.4129, device='cuda:0'), 'validation_loss_bbox': tensor(0.1373, device='cuda:0'), 'validation_loss_giou': tensor(0.4801, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
|
| 75 |
+
{'training_loss': tensor(2.0215, device='cuda:0'), 'train_loss_ce': tensor(0.3352, device='cuda:0'), 'train_loss_bbox': tensor(0.1555, device='cuda:0'), 'train_loss_giou': tensor(0.4544, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.0185, device='cuda:0'), 'validation_loss_ce': tensor(0.4065, device='cuda:0'), 'validation_loss_bbox': tensor(0.1314, device='cuda:0'), 'validation_loss_giou': tensor(0.4776, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
|
| 76 |
+
{'training_loss': tensor(1.6743, device='cuda:0'), 'train_loss_ce': tensor(0.3426, device='cuda:0'), 'train_loss_bbox': tensor(0.1190, device='cuda:0'), 'train_loss_giou': tensor(0.3684, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.0313, device='cuda:0'), 'validation_loss_ce': tensor(0.4118, device='cuda:0'), 'validation_loss_bbox': tensor(0.1326, device='cuda:0'), 'validation_loss_giou': tensor(0.4783, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
|
| 77 |
+
{'training_loss': tensor(1.8567, device='cuda:0'), 'train_loss_ce': tensor(0.4396, device='cuda:0'), 'train_loss_bbox': tensor(0.1169, device='cuda:0'), 'train_loss_giou': tensor(0.4164, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.0396, device='cuda:0'), 'validation_loss_ce': tensor(0.4058, device='cuda:0'), 'validation_loss_bbox': tensor(0.1364, device='cuda:0'), 'validation_loss_giou': tensor(0.4759, device='cuda:0'), 'validation_cardinality_error': tensor(1.1114, device='cuda:0')}
|
| 78 |
+
{'training_loss': tensor(1.8860, device='cuda:0'), 'train_loss_ce': tensor(0.3853, device='cuda:0'), 'train_loss_bbox': tensor(0.1128, device='cuda:0'), 'train_loss_giou': tensor(0.4683, device='cuda:0'), 'train_cardinality_error': tensor(0.5625, device='cuda:0'), 'validation_loss': tensor(1.9951, device='cuda:0'), 'validation_loss_ce': tensor(0.4074, device='cuda:0'), 'validation_loss_bbox': tensor(0.1306, device='cuda:0'), 'validation_loss_giou': tensor(0.4674, device='cuda:0'), 'validation_cardinality_error': tensor(0.4841, device='cuda:0')}
|
| 79 |
+
{'training_loss': tensor(2.0205, device='cuda:0'), 'train_loss_ce': tensor(0.4927, device='cuda:0'), 'train_loss_bbox': tensor(0.1259, device='cuda:0'), 'train_loss_giou': tensor(0.4492, device='cuda:0'), 'train_cardinality_error': tensor(0.6875, device='cuda:0'), 'validation_loss': tensor(1.9595, device='cuda:0'), 'validation_loss_ce': tensor(0.4047, device='cuda:0'), 'validation_loss_bbox': tensor(0.1282, device='cuda:0'), 'validation_loss_giou': tensor(0.4569, device='cuda:0'), 'validation_cardinality_error': tensor(0.7114, device='cuda:0')}
|
| 80 |
+
{'training_loss': tensor(1.9582, device='cuda:0'), 'train_loss_ce': tensor(0.4814, device='cuda:0'), 'train_loss_bbox': tensor(0.1253, device='cuda:0'), 'train_loss_giou': tensor(0.4251, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(1.9515, device='cuda:0'), 'validation_loss_ce': tensor(0.4023, device='cuda:0'), 'validation_loss_bbox': tensor(0.1285, device='cuda:0'), 'validation_loss_giou': tensor(0.4534, device='cuda:0'), 'validation_cardinality_error': tensor(1.1182, device='cuda:0')}
|
| 81 |
+
{'training_loss': tensor(1.7791, device='cuda:0'), 'train_loss_ce': tensor(0.4164, device='cuda:0'), 'train_loss_bbox': tensor(0.0951, device='cuda:0'), 'train_loss_giou': tensor(0.4437, device='cuda:0'), 'train_cardinality_error': tensor(0.2500, device='cuda:0'), 'validation_loss': tensor(1.9378, device='cuda:0'), 'validation_loss_ce': tensor(0.4027, device='cuda:0'), 'validation_loss_bbox': tensor(0.1279, device='cuda:0'), 'validation_loss_giou': tensor(0.4477, device='cuda:0'), 'validation_cardinality_error': tensor(0.4250, device='cuda:0')}
|
| 82 |
+
{'training_loss': tensor(1.9682, device='cuda:0'), 'train_loss_ce': tensor(0.4239, device='cuda:0'), 'train_loss_bbox': tensor(0.1232, device='cuda:0'), 'train_loss_giou': tensor(0.4641, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(1.8919, device='cuda:0'), 'validation_loss_ce': tensor(0.3992, device='cuda:0'), 'validation_loss_bbox': tensor(0.1212, device='cuda:0'), 'validation_loss_giou': tensor(0.4435, device='cuda:0'), 'validation_cardinality_error': tensor(1.0250, device='cuda:0')}
|
| 83 |
+
{'training_loss': tensor(1.8836, device='cuda:0'), 'train_loss_ce': tensor(0.4428, device='cuda:0'), 'train_loss_bbox': tensor(0.1272, device='cuda:0'), 'train_loss_giou': tensor(0.4025, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(1.9213, device='cuda:0'), 'validation_loss_ce': tensor(0.3993, device='cuda:0'), 'validation_loss_bbox': tensor(0.1226, device='cuda:0'), 'validation_loss_giou': tensor(0.4545, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
|
| 84 |
+
{'training_loss': tensor(1.7962, device='cuda:0'), 'train_loss_ce': tensor(0.4835, device='cuda:0'), 'train_loss_bbox': tensor(0.1070, device='cuda:0'), 'train_loss_giou': tensor(0.3888, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(1.9724, device='cuda:0'), 'validation_loss_ce': tensor(0.4014, device='cuda:0'), 'validation_loss_bbox': tensor(0.1263, device='cuda:0'), 'validation_loss_giou': tensor(0.4697, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
|
| 85 |
+
{'training_loss': tensor(1.7129, device='cuda:0'), 'train_loss_ce': tensor(0.4166, device='cuda:0'), 'train_loss_bbox': tensor(0.1019, device='cuda:0'), 'train_loss_giou': tensor(0.3934, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(1.8892, device='cuda:0'), 'validation_loss_ce': tensor(0.3976, device='cuda:0'), 'validation_loss_bbox': tensor(0.1195, device='cuda:0'), 'validation_loss_giou': tensor(0.4470, device='cuda:0'), 'validation_cardinality_error': tensor(0.9750, device='cuda:0')}
|
| 86 |
+
{'training_loss': tensor(1.9387, device='cuda:0'), 'train_loss_ce': tensor(0.5361, device='cuda:0'), 'train_loss_bbox': tensor(0.1148, device='cuda:0'), 'train_loss_giou': tensor(0.4143, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(1.9228, device='cuda:0'), 'validation_loss_ce': tensor(0.3983, device='cuda:0'), 'validation_loss_bbox': tensor(0.1237, device='cuda:0'), 'validation_loss_giou': tensor(0.4531, device='cuda:0'), 'validation_cardinality_error': tensor(1.0568, device='cuda:0')}
|
| 87 |
+
{'training_loss': tensor(1.9323, device='cuda:0'), 'train_loss_ce': tensor(0.4248, device='cuda:0'), 'train_loss_bbox': tensor(0.1176, device='cuda:0'), 'train_loss_giou': tensor(0.4599, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(1.8603, device='cuda:0'), 'validation_loss_ce': tensor(0.3975, device='cuda:0'), 'validation_loss_bbox': tensor(0.1190, device='cuda:0'), 'validation_loss_giou': tensor(0.4338, device='cuda:0'), 'validation_cardinality_error': tensor(1.1114, device='cuda:0')}
|
| 88 |
+
{'training_loss': tensor(1.9526, device='cuda:0'), 'train_loss_ce': tensor(0.4262, device='cuda:0'), 'train_loss_bbox': tensor(0.1383, device='cuda:0'), 'train_loss_giou': tensor(0.4173, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(1.8262, device='cuda:0'), 'validation_loss_ce': tensor(0.3934, device='cuda:0'), 'validation_loss_bbox': tensor(0.1146, device='cuda:0'), 'validation_loss_giou': tensor(0.4299, device='cuda:0'), 'validation_cardinality_error': tensor(0.9727, device='cuda:0')}
|
| 89 |
+
{'training_loss': tensor(1.7325, device='cuda:0'), 'train_loss_ce': tensor(0.3357, device='cuda:0'), 'train_loss_bbox': tensor(0.1189, device='cuda:0'), 'train_loss_giou': tensor(0.4012, device='cuda:0'), 'train_cardinality_error': tensor(0.3750, device='cuda:0'), 'validation_loss': tensor(1.7981, device='cuda:0'), 'validation_loss_ce': tensor(0.3921, device='cuda:0'), 'validation_loss_bbox': tensor(0.1107, device='cuda:0'), 'validation_loss_giou': tensor(0.4262, device='cuda:0'), 'validation_cardinality_error': tensor(0.4477, device='cuda:0')}
|
| 90 |
+
{'training_loss': tensor(1.9715, device='cuda:0'), 'train_loss_ce': tensor(0.4642, device='cuda:0'), 'train_loss_bbox': tensor(0.1204, device='cuda:0'), 'train_loss_giou': tensor(0.4525, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(1.7847, device='cuda:0'), 'validation_loss_ce': tensor(0.3908, device='cuda:0'), 'validation_loss_bbox': tensor(0.1122, device='cuda:0'), 'validation_loss_giou': tensor(0.4166, device='cuda:0'), 'validation_cardinality_error': tensor(0.9886, device='cuda:0')}
|
| 91 |
+
{'training_loss': tensor(1.6786, device='cuda:0'), 'train_loss_ce': tensor(0.3999, device='cuda:0'), 'train_loss_bbox': tensor(0.1044, device='cuda:0'), 'train_loss_giou': tensor(0.3783, device='cuda:0'), 'train_cardinality_error': tensor(0.4375, device='cuda:0'), 'validation_loss': tensor(1.7931, device='cuda:0'), 'validation_loss_ce': tensor(0.3867, device='cuda:0'), 'validation_loss_bbox': tensor(0.1113, device='cuda:0'), 'validation_loss_giou': tensor(0.4249, device='cuda:0'), 'validation_cardinality_error': tensor(0.4455, device='cuda:0')}
|
| 92 |
+
{'training_loss': tensor(1.7158, device='cuda:0'), 'train_loss_ce': tensor(0.4146, device='cuda:0'), 'train_loss_bbox': tensor(0.1021, device='cuda:0'), 'train_loss_giou': tensor(0.3954, device='cuda:0'), 'train_cardinality_error': tensor(0.3750, device='cuda:0'), 'validation_loss': tensor(1.8713, device='cuda:0'), 'validation_loss_ce': tensor(0.3841, device='cuda:0'), 'validation_loss_bbox': tensor(0.1178, device='cuda:0'), 'validation_loss_giou': tensor(0.4491, device='cuda:0'), 'validation_cardinality_error': tensor(0.3545, device='cuda:0')}
|
| 93 |
+
{'training_loss': tensor(1.9824, device='cuda:0'), 'train_loss_ce': tensor(0.4213, device='cuda:0'), 'train_loss_bbox': tensor(0.1372, device='cuda:0'), 'train_loss_giou': tensor(0.4375, device='cuda:0'), 'train_cardinality_error': tensor(0.8125, device='cuda:0'), 'validation_loss': tensor(1.8017, device='cuda:0'), 'validation_loss_ce': tensor(0.3884, device='cuda:0'), 'validation_loss_bbox': tensor(0.1127, device='cuda:0'), 'validation_loss_giou': tensor(0.4249, device='cuda:0'), 'validation_cardinality_error': tensor(0.5636, device='cuda:0')}
|
| 94 |
+
{'training_loss': tensor(1.9667, device='cuda:0'), 'train_loss_ce': tensor(0.4088, device='cuda:0'), 'train_loss_bbox': tensor(0.1550, device='cuda:0'), 'train_loss_giou': tensor(0.3914, device='cuda:0'), 'train_cardinality_error': tensor(0.5625, device='cuda:0'), 'validation_loss': tensor(2.0829, device='cuda:0'), 'validation_loss_ce': tensor(0.3969, device='cuda:0'), 'validation_loss_bbox': tensor(0.1408, device='cuda:0'), 'validation_loss_giou': tensor(0.4911, device='cuda:0'), 'validation_cardinality_error': tensor(0.4909, device='cuda:0')}
|
| 95 |
+
{'training_loss': tensor(1.9867, device='cuda:0'), 'train_loss_ce': tensor(0.4950, device='cuda:0'), 'train_loss_bbox': tensor(0.1075, device='cuda:0'), 'train_loss_giou': tensor(0.4771, device='cuda:0'), 'train_cardinality_error': tensor(0.6875, device='cuda:0'), 'validation_loss': tensor(1.8975, device='cuda:0'), 'validation_loss_ce': tensor(0.3880, device='cuda:0'), 'validation_loss_bbox': tensor(0.1216, device='cuda:0'), 'validation_loss_giou': tensor(0.4508, device='cuda:0'), 'validation_cardinality_error': tensor(0.3591, device='cuda:0')}
|
| 96 |
+
{'training_loss': tensor(1.9680, device='cuda:0'), 'train_loss_ce': tensor(0.3492, device='cuda:0'), 'train_loss_bbox': tensor(0.1332, device='cuda:0'), 'train_loss_giou': tensor(0.4765, device='cuda:0'), 'train_cardinality_error': tensor(0.8750, device='cuda:0'), 'validation_loss': tensor(1.8247, device='cuda:0'), 'validation_loss_ce': tensor(0.3879, device='cuda:0'), 'validation_loss_bbox': tensor(0.1151, device='cuda:0'), 'validation_loss_giou': tensor(0.4306, device='cuda:0'), 'validation_cardinality_error': tensor(0.8341, device='cuda:0')}
|
| 97 |
+
{'training_loss': tensor(1.6024, device='cuda:0'), 'train_loss_ce': tensor(0.4099, device='cuda:0'), 'train_loss_bbox': tensor(0.0864, device='cuda:0'), 'train_loss_giou': tensor(0.3803, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(1.8380, device='cuda:0'), 'validation_loss_ce': tensor(0.3858, device='cuda:0'), 'validation_loss_bbox': tensor(0.1171, device='cuda:0'), 'validation_loss_giou': tensor(0.4333, device='cuda:0'), 'validation_cardinality_error': tensor(0.8205, device='cuda:0')}
|
| 98 |
+
{'training_loss': tensor(1.4670, device='cuda:0'), 'train_loss_ce': tensor(0.3428, device='cuda:0'), 'train_loss_bbox': tensor(0.1047, device='cuda:0'), 'train_loss_giou': tensor(0.3002, device='cuda:0'), 'train_cardinality_error': tensor(0.7500, device='cuda:0'), 'validation_loss': tensor(1.8503, device='cuda:0'), 'validation_loss_ce': tensor(0.3915, device='cuda:0'), 'validation_loss_bbox': tensor(0.1159, device='cuda:0'), 'validation_loss_giou': tensor(0.4397, device='cuda:0'), 'validation_cardinality_error': tensor(0.8159, device='cuda:0')}
|
| 99 |
+
{'training_loss': tensor(1.5711, device='cuda:0'), 'train_loss_ce': tensor(0.2793, device='cuda:0'), 'train_loss_bbox': tensor(0.1109, device='cuda:0'), 'train_loss_giou': tensor(0.3687, device='cuda:0'), 'train_cardinality_error': tensor(0.8750, device='cuda:0'), 'validation_loss': tensor(1.7952, device='cuda:0'), 'validation_loss_ce': tensor(0.3900, device='cuda:0'), 'validation_loss_bbox': tensor(0.1118, device='cuda:0'), 'validation_loss_giou': tensor(0.4230, device='cuda:0'), 'validation_cardinality_error': tensor(0.8727, device='cuda:0')}
|
| 100 |
+
```
|