rt-detr-v2_barcode-detection

benjamintli/rt-detr-v2_barcode-detection

rt-detr-v2_barcode-detection is a object detection model from benjamintli. Use it when you need objects located in an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Object Detection
Library: transformers
License: apache-2.0
Model type: rt_detr_v2
Access: Public
Created: Jan 9, 2026
Updated: Jan 10, 2026
SHA: fb2c73c8

Base models

PekingU/rtdetr_v2_r18vd

Model card

From the Hugging Face model README

rt-detr-v2_barcode-detection

This model is a fine-tuned version of PekingU/rtdetr_v2_r18vd on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 5.0340
Map: 0.6583
Map 50: 0.8036
Map 75: 0.7156
Map Small: 0.2754
Map Medium: 0.7152
Map Large: 0.747
Mar 1: 0.3589
Mar 10: 0.833
Mar 100: 0.8673
Mar Small: 0.6183
Mar Medium: 0.8656
Mar Large: 0.8872
Map Barcode: 0.6583
Mar 100 Barcode: 0.8673

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 300
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Map	Map 50	Map 75	Map Barcode	Map Large	Map Medium	Map Small	Mar 1	Mar 10	Mar 100	Mar 100 Barcode	Mar Large	Mar Medium	Mar Small
7.43	1.0	1636	5.0547	0.623	0.7756	0.6841	0.623	0.6594	0.6674	0.2648	0.3542	0.8117	0.8521	0.8521	0.8749	0.8552	0.5325
6.9538	2.0	3272	4.9508	0.6297	0.7829	0.6878	0.6297	0.7109	0.6449	0.261	0.3612	0.8238	0.8604	0.8604	0.8794	0.8624	0.5972
6.6733	3.0	4908	5.0056	0.6553	0.8073	0.7122	0.6553	0.7359	0.6782	0.2319	0.3481	0.8201	0.8542	0.8542	0.8712	0.8573	0.6107
6.5783	4.0	6544	5.0493	0.6524	0.808	0.711	0.6524	0.7472	0.6782	0.2391	0.3581	0.8268	0.8629	0.8629	0.8819	0.8639	0.6066
6.4986	5.0	8180	5.0208	0.6944	0.8578	0.7542	0.6944	0.7651	0.7135	0.2808	0.3706	0.8307	0.8611	0.8611	0.879	0.863	0.6131
6.4056	6.0	9816	5.0116	0.6843	0.8399	0.7445	0.6843	0.7607	0.7126	0.3026	0.371	0.8374	0.8664	0.8664	0.8864	0.8646	0.6176
6.4074	7.0	11452	5.0229	0.653	0.7989	0.7106	0.2768	0.7112	0.731	0.3513	0.8326	0.8694	0.619	0.8675	0.8896	0.653	0.8694
6.2576	8.0	13088	5.0340	0.6583	0.8036	0.7156	0.2754	0.7152	0.747	0.3589	0.833	0.8673	0.6183	0.8656	0.8872	0.6583	0.8673

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.4.2
Tokenizers 0.22.1

Task: Object Detection
Library: transformers
Type: rt_detr_v2
License: apache-2.0
Created: Jan 9, 2026
Updated: Jan 10, 2026