rtdetr-vehicle-accident-detection

dri11heaD/rtdetr-vehicle-accident-detection

rtdetr-vehicle-accident-detection is a object detection model from dri11heaD. 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
Access: Public
Created: Aug 20, 2026
Updated: Aug 20, 2026
SHA: c93ff7b3

Base models

PekingU/rtdetr_r50vd_coco_o365

Model card

From the Hugging Face model README

rtdetr-vehicle-accident-detection

This model is a fine-tuned version of PekingU/rtdetr_r50vd_coco_o365 on the None dataset. It achieves the following results on the evaluation set:

Loss: 12.2411
Map: 0.4396
Map 50: 0.5998
Map 75: 0.4789
Map Small: 0.3192
Map Medium: 0.3353
Map Large: 0.5358
Mar 1: 0.3873
Mar 10: 0.6599
Mar 100: 0.7769
Mar Small: 0.5733
Mar Medium: 0.7379
Mar Large: 0.846
Map Accident: 0.5871
Mar 100 Accident: 0.8212
Map Non-accident: 0.2922
Mar 100 Non-accident: 0.7326

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: 0.0001
train_batch_size: 4
eval_batch_size: 4
seed: 3407
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: cosine
lr_scheduler_warmup_steps: 300
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Map	Map 50	Map 75	Map Small	Map Medium	Map Large	Mar 1	Mar 10	Mar 100	Mar Small	Mar Medium	Mar Large	Map Accident	Mar 100 Accident	Map Non-accident	Mar 100 Non-accident
34.3857	1.0	147	17.0306	0.1287	0.2164	0.1281	0.0152	0.0507	0.2043	0.1579	0.4775	0.6838	0.3933	0.6255	0.7562	0.2205	0.7451	0.0369	0.6225
23.2918	2.0	294	13.6842	0.2082	0.3272	0.2125	0.1027	0.1241	0.235	0.2401	0.5515	0.7359	0.4633	0.6905	0.7985	0.349	0.787	0.0674	0.6848
20.2538	3.0	441	15.5058	0.1086	0.1863	0.1037	0.162	0.1085	0.118	0.1705	0.4925	0.7317	0.48	0.7353	0.7556	0.1776	0.7611	0.0396	0.7022
18.6402	4.0	588	12.7415	0.2555	0.3774	0.2743	0.1527	0.1933	0.2796	0.2697	0.5975	0.7796	0.5133	0.7421	0.8368	0.4315	0.8207	0.0796	0.7384
18.0487	5.0	735	12.7144	0.3171	0.4477	0.3396	0.3157	0.2134	0.3409	0.3292	0.6712	0.7894	0.5533	0.7539	0.8465	0.491	0.8332	0.1431	0.7457
16.2050	6.0	882	12.1642	0.3583	0.5194	0.3917	0.392	0.294	0.4254	0.3362	0.658	0.7727	0.5	0.725	0.8361	0.5061	0.8171	0.2106	0.7283
15.4431	7.0	1029	11.9625	0.3941	0.5309	0.4366	0.313	0.31	0.4255	0.3691	0.6622	0.803	0.5033	0.7737	0.8682	0.5588	0.8358	0.2294	0.7703
13.9417	8.0	1176	11.7418	0.413	0.5827	0.4482	0.3636	0.2982	0.469	0.3611	0.6722	0.7738	0.58	0.732	0.8287	0.5484	0.8259	0.2776	0.7217
13.9773	9.0	1323	11.7699	0.4285	0.5919	0.4735	0.3905	0.3132	0.4907	0.3515	0.6647	0.7739	0.5567	0.7324	0.851	0.5641	0.8254	0.293	0.7225
13.5177	10.0	1470	11.5481	0.424	0.5776	0.4673	0.3623	0.2948	0.5155	0.3689	0.6762	0.7814	0.59	0.7399	0.8432	0.594	0.8295	0.254	0.7333
12.8414	11.0	1617	11.9601	0.4462	0.6045	0.4926	0.4114	0.3458	0.5228	0.3879	0.6826	0.7958	0.6067	0.7577	0.8593	0.6001	0.843	0.2924	0.7486
11.1679	12.0	1764	11.5837	0.4502	0.6095	0.4951	0.3434	0.3507	0.5305	0.3946	0.6792	0.7929	0.6433	0.7556	0.8412	0.6011	0.8337	0.2992	0.7522
10.4115	13.0	1911	12.0687	0.4393	0.6029	0.4926	0.2706	0.3286	0.5283	0.3735	0.6784	0.7765	0.5433	0.7361	0.8429	0.5885	0.8269	0.29	0.7261
10.1284	14.0	2058	11.9256	0.4471	0.6075	0.497	0.3799	0.3347	0.5352	0.3925	0.6833	0.7841	0.6	0.7351	0.8435	0.5957	0.829	0.2984	0.7391
9.7026	15.0	2205	11.9128	0.4461	0.6111	0.4978	0.3536	0.3341	0.5414	0.3823	0.6731	0.7796	0.6233	0.7321	0.8432	0.5997	0.8352	0.2926	0.7239
9.9951	16.0	2352	12.1509	0.4522	0.6193	0.4912	0.3841	0.3506	0.5359	0.3836	0.6733	0.785	0.6067	0.7305	0.8533	0.5956	0.8264	0.3088	0.7435
9.4406	17.0	2499	12.2262	0.4372	0.598	0.4804	0.3589	0.3363	0.525	0.385	0.6574	0.7792	0.5867	0.7358	0.8399	0.5817	0.8192	0.2927	0.7391
9.2950	18.0	2646	12.2601	0.4433	0.6035	0.481	0.333	0.3401	0.5386	0.3883	0.6713	0.776	0.5933	0.7282	0.8412	0.5918	0.8238	0.2948	0.7283
9.1047	19.0	2793	12.2527	0.4402	0.6011	0.4765	0.3246	0.3365	0.5359	0.3873	0.6678	0.7821	0.5767	0.7443	0.847	0.5878	0.8228	0.2926	0.7413
8.4988	20.0	2940	12.2411	0.4396	0.5998	0.4789	0.3192	0.3353	0.5358	0.3873	0.6599	0.7769	0.5733	0.7379	0.846	0.5871	0.8212	0.2922	0.7326

Framework versions

Transformers 5.15.1
Pytorch 2.11.0+cu128
Datasets 5.0.1
Tokenizers 0.22.2

Task: Object Detection
Library: transformers
Type: rt_detr
License: apache-2.0
Created: Aug 20, 2026
Updated: Aug 20, 2026