detr-resnet-50_finetuned_cppe5

This model is a fine-tuned version of facebook/detr-resnet-50 on cppe5 dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and testing data

CPPE5 dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Accumulating evaluation results...

DONE (t=0.02s).

IoU metric: bbox

Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.272

Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.504

Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.254

Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.131

Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.154

Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.300

Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.264

Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.446

Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.455

Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.143

Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.265

Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.516

Framework versions

• Transformers 4.39.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2