hustvl/yolos-base · mAP Drop

I tried to reproduce the results mentioned on this model card. Seems like my results do not match the claimed mAP in the model card. I cannot figure out how to get the correct numbers, can you help me find my mistake?

Claimed mAP: 42.0
Recieved mAP: 36.6

Here are the details for my validation:

I instantiate pre-trained model with transformers.pipeline() and use COCO API to calculate AP from detection bboxes.
Evaluation was performed on macOS CPU.
Dataset was downloaded from cocodataset.org

 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.366
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.567
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.379
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.144
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.397
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.303
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.441
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.452
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.193
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.491
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.687