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--- |
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library_name: transformers |
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tags: [] |
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--- |
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## Original 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 ] = 0.000 |
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000 |
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Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000 |
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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 ] = 0.001 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.008 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.017 |
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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 ] = 0.017 |
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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 ] = 0.003 |
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.007 |
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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 ] = 0.000 |
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Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.003 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.024 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.066 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.070 |
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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 ] = 0.071 |
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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: 3 |
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## Logging |
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### Training process |
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``` |
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{'training_loss': tensor(2.0822, device='cuda:0'), 'train_loss_ce': tensor(0.5032, device='cuda:0'), 'train_loss_bbox': tensor(0.1356, device='cuda:0'), 'train_loss_giou': tensor(0.4505, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.3906, device='cuda:0'), 'validation_loss_ce': tensor(0.5131, device='cuda:0'), 'validation_loss_bbox': tensor(0.1641, device='cuda:0'), 'validation_loss_giou': tensor(0.5285, device='cuda:0'), 'validation_cardinality_error': tensor(1.1227, device='cuda:0')} |
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{'training_loss': tensor(2.5546, device='cuda:0'), 'train_loss_ce': tensor(0.5681, device='cuda:0'), 'train_loss_bbox': tensor(0.1646, device='cuda:0'), 'train_loss_giou': tensor(0.5818, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.4028, device='cuda:0'), 'validation_loss_ce': tensor(0.5090, device='cuda:0'), 'validation_loss_bbox': tensor(0.1696, device='cuda:0'), 'validation_loss_giou': tensor(0.5230, device='cuda:0'), 'validation_cardinality_error': tensor(1.1227, device='cuda:0')} |
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{'training_loss': tensor(2.4528, device='cuda:0'), 'train_loss_ce': tensor(0.4475, device='cuda:0'), 'train_loss_bbox': tensor(0.1614, device='cuda:0'), 'train_loss_giou': tensor(0.5991, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3522, device='cuda:0'), 'validation_loss_ce': tensor(0.4847, device='cuda:0'), 'validation_loss_bbox': tensor(0.1584, device='cuda:0'), 'validation_loss_giou': tensor(0.5377, device='cuda:0'), 'validation_cardinality_error': tensor(1.1227, device='cuda:0')} |
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``` |
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### Validation process |
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``` |
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{'validation_loss': tensor(6.1819, device='cuda:0'), 'validation_loss_ce': tensor(2.1987, device='cuda:0'), 'validation_loss_bbox': tensor(0.4528, device='cuda:0'), 'validation_loss_giou': tensor(0.8597, device='cuda:0'), 'validation_cardinality_error': tensor(97.7500, device='cuda:0')} |
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{'training_loss': tensor(2.0822, device='cuda:0'), 'train_loss_ce': tensor(0.5032, device='cuda:0'), 'train_loss_bbox': tensor(0.1356, device='cuda:0'), 'train_loss_giou': tensor(0.4505, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.3906, device='cuda:0'), 'validation_loss_ce': tensor(0.5131, device='cuda:0'), 'validation_loss_bbox': tensor(0.1641, device='cuda:0'), 'validation_loss_giou': tensor(0.5285, device='cuda:0'), 'validation_cardinality_error': tensor(1.1227, device='cuda:0')} |
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{'training_loss': tensor(2.5546, device='cuda:0'), 'train_loss_ce': tensor(0.5681, device='cuda:0'), 'train_loss_bbox': tensor(0.1646, device='cuda:0'), 'train_loss_giou': tensor(0.5818, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.4028, device='cuda:0'), 'validation_loss_ce': tensor(0.5090, device='cuda:0'), 'validation_loss_bbox': tensor(0.1696, device='cuda:0'), 'validation_loss_giou': tensor(0.5230, device='cuda:0'), 'validation_cardinality_error': tensor(1.1227, device='cuda:0')} |
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{'training_loss': tensor(2.4528, device='cuda:0'), 'train_loss_ce': tensor(0.4475, device='cuda:0'), 'train_loss_bbox': tensor(0.1614, device='cuda:0'), 'train_loss_giou': tensor(0.5991, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3522, device='cuda:0'), 'validation_loss_ce': tensor(0.4847, device='cuda:0'), 'validation_loss_bbox': tensor(0.1584, device='cuda:0'), 'validation_loss_giou': tensor(0.5377, device='cuda:0'), 'validation_cardinality_error': tensor(1.1227, device='cuda:0')} |
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``` |
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