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@@ -3,197 +3,150 @@ library_name: transformers
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  ---
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- # Model Card for Model ID
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- ## How to Get Started with the Model
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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 ] = 0.011
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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 ] = 0.011
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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 ] = 0.005
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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 ] = 0.001
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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 ] = 0.005
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.036
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.131
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.141
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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 ] = 0.145
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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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+ - dropout_rate: 0.3
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+ - weight_decay: 0.01
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+ - max_epochs: 100
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+
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+ ## Logging
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+ ### Training process
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+ ```
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+ {'validation_loss': tensor(5.9922, device='cuda:0'), 'validation_loss_ce': tensor(1.9217, device='cuda:0'), 'validation_loss_bbox': tensor(0.4632, device='cuda:0'), 'validation_loss_giou': tensor(0.8772, device='cuda:0'), 'validation_cardinality_error': tensor(40.3438, device='cuda:0')}
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+ {'training_loss': tensor(3.1585, device='cuda:0'), 'train_loss_ce': tensor(0.5599, device='cuda:0'), 'train_loss_bbox': tensor(0.2764, device='cuda:0'), 'train_loss_giou': tensor(0.6083, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.7145, device='cuda:0'), 'validation_loss_ce': tensor(0.5435, device='cuda:0'), 'validation_loss_bbox': tensor(0.1939, device='cuda:0'), 'validation_loss_giou': tensor(0.6009, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.5024, device='cuda:0'), 'train_loss_ce': tensor(0.4082, device='cuda:0'), 'train_loss_bbox': tensor(0.1870, device='cuda:0'), 'train_loss_giou': tensor(0.5797, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3204, device='cuda:0'), 'validation_loss_ce': tensor(0.4753, device='cuda:0'), 'validation_loss_bbox': tensor(0.1581, device='cuda:0'), 'validation_loss_giou': tensor(0.5273, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(1.9285, device='cuda:0'), 'train_loss_ce': tensor(0.4730, device='cuda:0'), 'train_loss_bbox': tensor(0.1512, device='cuda:0'), 'train_loss_giou': tensor(0.3496, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3177, device='cuda:0'), 'validation_loss_ce': tensor(0.4526, device='cuda:0'), 'validation_loss_bbox': tensor(0.1578, device='cuda:0'), 'validation_loss_giou': tensor(0.5381, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.3199, device='cuda:0'), 'train_loss_ce': tensor(0.5028, device='cuda:0'), 'train_loss_bbox': tensor(0.1363, device='cuda:0'), 'train_loss_giou': tensor(0.5678, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3181, device='cuda:0'), 'validation_loss_ce': tensor(0.4481, device='cuda:0'), 'validation_loss_bbox': tensor(0.1617, device='cuda:0'), 'validation_loss_giou': tensor(0.5307, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.1901, device='cuda:0'), 'train_loss_ce': tensor(0.4650, device='cuda:0'), 'train_loss_bbox': tensor(0.1622, device='cuda:0'), 'train_loss_giou': tensor(0.4570, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2432, device='cuda:0'), 'validation_loss_ce': tensor(0.4404, device='cuda:0'), 'validation_loss_bbox': tensor(0.1573, device='cuda:0'), 'validation_loss_giou': tensor(0.5082, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.0616, device='cuda:0'), 'train_loss_ce': tensor(0.4577, device='cuda:0'), 'train_loss_bbox': tensor(0.1421, device='cuda:0'), 'train_loss_giou': tensor(0.4467, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2807, device='cuda:0'), 'validation_loss_ce': tensor(0.4421, device='cuda:0'), 'validation_loss_bbox': tensor(0.1580, device='cuda:0'), 'validation_loss_giou': tensor(0.5242, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.2789, device='cuda:0'), 'train_loss_ce': tensor(0.4960, device='cuda:0'), 'train_loss_bbox': tensor(0.1681, device='cuda:0'), 'train_loss_giou': tensor(0.4712, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2138, device='cuda:0'), 'validation_loss_ce': tensor(0.4347, device='cuda:0'), 'validation_loss_bbox': tensor(0.1486, device='cuda:0'), 'validation_loss_giou': tensor(0.5181, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(1.9775, device='cuda:0'), 'train_loss_ce': tensor(0.4219, device='cuda:0'), 'train_loss_bbox': tensor(0.1393, device='cuda:0'), 'train_loss_giou': tensor(0.4297, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3134, device='cuda:0'), 'validation_loss_ce': tensor(0.4302, device='cuda:0'), 'validation_loss_bbox': tensor(0.1644, device='cuda:0'), 'validation_loss_giou': tensor(0.5307, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(1.7083, device='cuda:0'), 'train_loss_ce': tensor(0.4728, device='cuda:0'), 'train_loss_bbox': tensor(0.1055, device='cuda:0'), 'train_loss_giou': tensor(0.3539, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2964, device='cuda:0'), 'validation_loss_ce': tensor(0.4320, device='cuda:0'), 'validation_loss_bbox': tensor(0.1584, device='cuda:0'), 'validation_loss_giou': tensor(0.5362, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.2199, device='cuda:0'), 'train_loss_ce': tensor(0.3609, device='cuda:0'), 'train_loss_bbox': tensor(0.1701, device='cuda:0'), 'train_loss_giou': tensor(0.5041, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2740, device='cuda:0'), 'validation_loss_ce': tensor(0.4260, device='cuda:0'), 'validation_loss_bbox': tensor(0.1623, device='cuda:0'), 'validation_loss_giou': tensor(0.5182, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.5320, device='cuda:0'), 'train_loss_ce': tensor(0.3962, device='cuda:0'), 'train_loss_bbox': tensor(0.1901, device='cuda:0'), 'train_loss_giou': tensor(0.5926, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1716, device='cuda:0'), 'validation_loss_ce': tensor(0.4206, device='cuda:0'), 'validation_loss_bbox': tensor(0.1498, device='cuda:0'), 'validation_loss_giou': tensor(0.5009, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(1.8947, device='cuda:0'), 'train_loss_ce': tensor(0.3639, device='cuda:0'), 'train_loss_bbox': tensor(0.1444, device='cuda:0'), 'train_loss_giou': tensor(0.4044, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2001, device='cuda:0'), 'validation_loss_ce': tensor(0.4262, device='cuda:0'), 'validation_loss_bbox': tensor(0.1507, device='cuda:0'), 'validation_loss_giou': tensor(0.5101, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.1039, device='cuda:0'), 'train_loss_ce': tensor(0.4785, device='cuda:0'), 'train_loss_bbox': tensor(0.1239, device='cuda:0'), 'train_loss_giou': tensor(0.5030, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1841, device='cuda:0'), 'validation_loss_ce': tensor(0.4133, device='cuda:0'), 'validation_loss_bbox': tensor(0.1467, device='cuda:0'), 'validation_loss_giou': tensor(0.5186, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.4880, device='cuda:0'), 'train_loss_ce': tensor(0.4607, device='cuda:0'), 'train_loss_bbox': tensor(0.1564, device='cuda:0'), 'train_loss_giou': tensor(0.6227, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3479, device='cuda:0'), 'validation_loss_ce': tensor(0.4191, device='cuda:0'), 'validation_loss_bbox': tensor(0.1716, device='cuda:0'), 'validation_loss_giou': tensor(0.5355, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.0206, device='cuda:0'), 'train_loss_ce': tensor(0.3709, device='cuda:0'), 'train_loss_bbox': tensor(0.1387, device='cuda:0'), 'train_loss_giou': tensor(0.4780, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1861, device='cuda:0'), 'validation_loss_ce': tensor(0.4140, device='cuda:0'), 'validation_loss_bbox': tensor(0.1535, device='cuda:0'), 'validation_loss_giou': tensor(0.5023, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.0864, device='cuda:0'), 'train_loss_ce': tensor(0.4814, device='cuda:0'), 'train_loss_bbox': tensor(0.1503, device='cuda:0'), 'train_loss_giou': tensor(0.4269, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2221, device='cuda:0'), 'validation_loss_ce': tensor(0.4118, device='cuda:0'), 'validation_loss_bbox': tensor(0.1502, device='cuda:0'), 'validation_loss_giou': tensor(0.5296, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.2339, device='cuda:0'), 'train_loss_ce': tensor(0.2700, device='cuda:0'), 'train_loss_bbox': tensor(0.1505, device='cuda:0'), 'train_loss_giou': tensor(0.6056, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1954, device='cuda:0'), 'validation_loss_ce': tensor(0.4094, device='cuda:0'), 'validation_loss_bbox': tensor(0.1499, device='cuda:0'), 'validation_loss_giou': tensor(0.5183, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(1.5445, device='cuda:0'), 'train_loss_ce': tensor(0.3648, device='cuda:0'), 'train_loss_bbox': tensor(0.0959, device='cuda:0'), 'train_loss_giou': tensor(0.3501, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2570, device='cuda:0'), 'validation_loss_ce': tensor(0.4029, device='cuda:0'), 'validation_loss_bbox': tensor(0.1562, device='cuda:0'), 'validation_loss_giou': tensor(0.5364, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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+ {'training_loss': tensor(2.1753, device='cuda:0'), 'train_loss_ce': tensor(0.3664, device='cuda:0'), 'train_loss_bbox': tensor(0.1394, device='cuda:0'), 'train_loss_giou': tensor(0.5559, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2393, device='cuda:0'), 'validation_loss_ce': tensor(0.4080, device='cuda:0'), 'validation_loss_bbox': tensor(0.1534, device='cuda:0'), 'validation_loss_giou': tensor(0.5322, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
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72
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77
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78
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79
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80
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81
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82
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83
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84
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85
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86
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87
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88
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89
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90
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91
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92
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93
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94
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95
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96
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97
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98
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99
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100
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101
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102
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103
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104
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105
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106
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107
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108
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109
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113
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115
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116
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117
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118
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119
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120
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121
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122
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123
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124
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125
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126
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127
+ {'training_loss': tensor(2.1641, device='cuda:0'), 'train_loss_ce': tensor(0.2473, device='cuda:0'), 'train_loss_bbox': tensor(0.1654, device='cuda:0'), 'train_loss_giou': tensor(0.5449, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1640, device='cuda:0'), 'validation_loss_ce': tensor(0.3883, device='cuda:0'), 'validation_loss_bbox': tensor(0.1466, device='cuda:0'), 'validation_loss_giou': tensor(0.5214, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
128
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129
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130
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131
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132
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133
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134
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135
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136
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137
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138
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139
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140
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141
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142
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143
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144
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145
+ {'training_loss': tensor(2.1892, device='cuda:0'), 'train_loss_ce': tensor(0.4731, device='cuda:0'), 'train_loss_bbox': tensor(0.1667, device='cuda:0'), 'train_loss_giou': tensor(0.4413, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1397, device='cuda:0'), 'validation_loss_ce': tensor(0.3913, device='cuda:0'), 'validation_loss_bbox': tensor(0.1409, device='cuda:0'), 'validation_loss_giou': tensor(0.5219, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
146
+ {'training_loss': tensor(1.6873, device='cuda:0'), 'train_loss_ce': tensor(0.2624, device='cuda:0'), 'train_loss_bbox': tensor(0.0988, device='cuda:0'), 'train_loss_giou': tensor(0.4655, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1196, device='cuda:0'), 'validation_loss_ce': tensor(0.3859, device='cuda:0'), 'validation_loss_bbox': tensor(0.1396, device='cuda:0'), 'validation_loss_giou': tensor(0.5178, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
147
+ {'training_loss': tensor(1.6725, device='cuda:0'), 'train_loss_ce': tensor(0.2990, device='cuda:0'), 'train_loss_bbox': tensor(0.1056, device='cuda:0'), 'train_loss_giou': tensor(0.4227, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.0944, device='cuda:0'), 'validation_loss_ce': tensor(0.3873, device='cuda:0'), 'validation_loss_bbox': tensor(0.1395, device='cuda:0'), 'validation_loss_giou': tensor(0.5047, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
148
+ {'training_loss': tensor(1.9737, device='cuda:0'), 'train_loss_ce': tensor(0.3862, device='cuda:0'), 'train_loss_bbox': tensor(0.1393, device='cuda:0'), 'train_loss_giou': tensor(0.4454, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1188, device='cuda:0'), 'validation_loss_ce': tensor(0.3850, device='cuda:0'), 'validation_loss_bbox': tensor(0.1409, device='cuda:0'), 'validation_loss_giou': tensor(0.5148, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
149
+ {'training_loss': tensor(1.9090, device='cuda:0'), 'train_loss_ce': tensor(0.3899, device='cuda:0'), 'train_loss_bbox': tensor(0.1334, device='cuda:0'), 'train_loss_giou': tensor(0.4259, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1303, device='cuda:0'), 'validation_loss_ce': tensor(0.3922, device='cuda:0'), 'validation_loss_bbox': tensor(0.1415, device='cuda:0'), 'validation_loss_giou': tensor(0.5154, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
150
+ {'training_loss': tensor(1.7123, device='cuda:0'), 'train_loss_ce': tensor(0.3532, device='cuda:0'), 'train_loss_bbox': tensor(0.1297, device='cuda:0'), 'train_loss_giou': tensor(0.3552, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1428, device='cuda:0'), 'validation_loss_ce': tensor(0.3844, device='cuda:0'), 'validation_loss_bbox': tensor(0.1410, device='cuda:0'), 'validation_loss_giou': tensor(0.5268, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
151
+ {'training_loss': tensor(1.5493, device='cuda:0'), 'train_loss_ce': tensor(0.3313, device='cuda:0'), 'train_loss_bbox': tensor(0.1282, device='cuda:0'), 'train_loss_giou': tensor(0.2885, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.1454, device='cuda:0'), 'validation_loss_ce': tensor(0.3884, device='cuda:0'), 'validation_loss_bbox': tensor(0.1415, device='cuda:0'), 'validation_loss_giou': tensor(0.5247, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
152
+ ```