learning_rate: 5e-05
train_batch_size: 8
eval_batch_size: 8
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: 12
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
13.9538	1.0	309	9.3017	0.1194	0.1975	0.1187	0.0005	0.0839	0.1319	0.2059	0.454	0.7321	0.1167	0.7256	0.755	0.212	0.7932	0.0267	0.671
10.9516	2.0	618	7.7241	0.1604	0.2364	0.1692	0.0046	0.1294	0.1721	0.2663	0.5475	0.7682	0.2033	0.7531	0.7882	0.2623	0.8098	0.0584	0.7265
9.7495	3.0	927	7.4023	0.2277	0.3323	0.2446	0.0027	0.2111	0.2466	0.2999	0.5443	0.7611	0.2167	0.7467	0.7647	0.402	0.8071	0.0534	0.7151
9.0010	4.0	1236	7.1968	0.2604	0.3866	0.2688	0.0033	0.2712	0.2747	0.3823	0.616	0.7804	0.2633	0.762	0.7846	0.4156	0.8163	0.1052	0.7445
8.1878	5.0	1545	7.3127	0.3201	0.4578	0.3438	0.0044	0.3368	0.3705	0.406	0.6326	0.8057	0.31	0.7894	0.8222	0.4969	0.838	0.1432	0.7735
7.6957	6.0	1854	7.1702	0.3381	0.4731	0.3851	0.0083	0.3387	0.4001	0.3991	0.6428	0.8036	0.3733	0.7875	0.8129	0.5361	0.841	0.1402	0.7661
7.2060	7.0	2163	7.1868	0.3748	0.5356	0.4141	0.0082	0.3765	0.4138	0.4068	0.6454	0.7854	0.3367	0.7818	0.7839	0.5359	0.8173	0.2136	0.7535
6.9991	8.0	2472	7.2713	0.3682	0.5264	0.4016	0.0091	0.3571	0.4085	0.4129	0.6504	0.7904	0.39	0.7895	0.7824	0.5473	0.8356	0.1892	0.7453
6.5298	9.0	2781	7.2003	0.399	0.5598	0.444	0.0092	0.3816	0.4531	0.4156	0.6427	0.7918	0.3467	0.7919	0.7889	0.5602	0.8339	0.2377	0.7498
6.3957	10.0	3090	7.3283	0.3835	0.5481	0.4221	0.0089	0.3827	0.4168	0.427	0.6367	0.7828	0.3567	0.7829	0.78	0.5509	0.8268	0.216	0.7388
6.2769	11.0	3399	7.2994	0.394	0.5562	0.434	0.0085	0.3767	0.4416	0.414	0.644	0.7889	0.3633	0.7847	0.7935	0.5563	0.8292	0.2316	0.7486
6.2947	12.0	3708	7.3092	0.3966	0.5632	0.4384	0.0078	0.3845	0.438	0.4148	0.6538	0.7869	0.3633	0.7854	0.7864	0.5535	0.8302	0.2396	0.7437

Framework versions

Transformers 5.15.0
Pytorch 2.11.0+cu128
Datasets 5.0.1
Tokenizers 0.22.2

dri11heaD/rtdetr-accident-cctv

rtdetr-accident-cctv

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

dri11heaD/
rtdetr-accident-cctv