---

library_name: transformers
tags: []
---

## Original result
```
IoU metric: bbox
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.001
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.004
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.011
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.012
```

## After training result
```
IoU metric: bbox
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.004
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.010
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.002
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.004
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.042
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.079
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.093
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.007
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.094
```

## Config
- dataset: NIH
- original model: facebook/detr-resnet-50
- lr: 0.0001
- max_epochs: 10

## Logging

### Training process
```

{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
```

### Validation process
```
{'validation_loss': tensor(6.4491, device='cuda:0'), 'validation_loss_ce': tensor(1.6310, device='cuda:0'), 'validation_loss_bbox': tensor(0.5587, device='cuda:0'), 'validation_loss_giou': tensor(1.0123, device='cuda:0'), 'validation_cardinality_error': tensor(8.9375, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training_loss': tensor(2.1957, device='cuda:0'), 'train_loss_ce': tensor(0.4394, device='cuda:0'), 'train_loss_bbox': tensor(0.1586, device='cuda:0'), 'train_loss_giou': tensor(0.4816, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2341, device='cuda:0'), 'validation_loss_ce': tensor(0.4642, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1.1295, device='cuda:0')}
{'training

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