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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 ] = -1.000 |
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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 ] = 0.000 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 |
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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 ] = 0.000 |
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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 ] = 0.001 |
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.002 |
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Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.001 |
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Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 |
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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 ] = 0.001 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.002 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.015 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.026 |
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Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000 |
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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 ] = 0.028 |
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``` |
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## Config |
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- dataset: NIH |
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- original model: hustvl/yolos-tiny |
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- lr: 0.0001 |
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- dropout_rate: 0.1 |
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- weight_decay: 0.001 |
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- max_epochs: 1 |
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- train samples: 885 |
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## Logging |
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### Training process |
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``` |
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{'validation_loss': tensor(7.2682, device='cuda:0'), 'validation_loss_ce': tensor(2.4654, device='cuda:0'), 'validation_loss_bbox': tensor(0.5599, device='cuda:0'), 'validation_loss_giou': tensor(1.0016, device='cuda:0'), 'validation_cardinality_error': tensor(99., device='cuda:0')} |
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{'training_loss': tensor(3.1491, device='cuda:0'), 'train_loss_ce': tensor(0.3927, device='cuda:0'), 'train_loss_bbox': tensor(0.2719, device='cuda:0'), 'train_loss_giou': tensor(0.6985, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2454, device='cuda:0'), 'validation_loss_ce': tensor(0.4346, device='cuda:0'), 'validation_loss_bbox': tensor(0.1519, device='cuda:0'), 'validation_loss_giou': tensor(0.5256, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')} |
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``` |
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## Examples |
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{'size': tensor([512, 512]), 'image_id': tensor([1]), 'class_labels': tensor([4]), 'boxes': tensor([[0.2622, 0.5729, 0.0847, 0.0773]]), 'area': tensor([1717.9431]), 'iscrowd': tensor([0]), 'orig_size': tensor([1024, 1024])} |
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