Modelpublic

merve/rfdetr-roadsign-agree1

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face

0likes36downloads

Model Card

rfdetr-roadsign-agree1

This model is a fine-tuned version of Roboflow/rf-detr-base on an unknown dataset. It achieves the following results on the evaluation set:

—Loss: 10.9431
—Map: 0.2977
—Map 50: 0.3348
—Map 75: 0.3316
—Map Small: -1.0
—Map Medium: 0.2581
—Map Large: 0.312
—Mar 1: 0.8002
—Mar 10: 0.914
—Mar 100: 0.9207
—Mar Small: -1.0
—Mar Medium: 0.7952
—Mar Large: 0.9256
—Map Bus Stop: 0.0168
—Mar 100 Bus Stop: 0.8
—Map Do Not Enter: 0.7351
—Mar 100 Do Not Enter: 0.9647
—Map Do Not Stop: 0.2201
—Mar 100 Do Not Stop: 0.9556
—Map Do Not Turn L: 0.6354
—Mar 100 Do Not Turn L: 0.95
—Map Do Not Turn R: 0.2183
—Mar 100 Do Not Turn R: 0.9625
—Map Do Not U Turn: 0.1473
—Mar 100 Do Not U Turn: 0.9556
—Map Enter Left Lane: 0.0736
—Mar 100 Enter Left Lane: 0.96
—Map Green Light: 0.6003
—Mar 100 Green Light: 0.85
—Map Left Right Lane: 0.6462
—Mar 100 Left Right Lane: 0.9462
—Map No Parking: 0.5851
—Mar 100 No Parking: 0.9357
—Map Parking: 0.4673
—Mar 100 Parking: 0.92
—Map Ped Crossing: 0.2841
—Mar 100 Ped Crossing: 0.9786
—Map Ped Zebra Cross: 0.1496
—Mar 100 Ped Zebra Cross: 1.0
—Map Railway Crossing: 0.1275
—Mar 100 Railway Crossing: 1.0
—Map Red Light: 0.264
—Mar 100 Red Light: 0.8421
—Map Stop: 0.1531
—Mar 100 Stop: 0.96
—Map T Intersection L: 0.1283
—Mar 100 T Intersection L: 0.9556
—Map Traffic Light: 0.0914
—Mar 100 Traffic Light: 0.7714
—Map U Turn: 0.3491
—Mar 100 U Turn: 0.8857
—Map Warning: 0.2874
—Mar 100 Warning: 0.9118
—Map Yellow Light: 0.0724
—Mar 100 Yellow Light: 0.8286

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
—trainbatchsize: 8
—evalbatchsize: 8
—seed: 42
—optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
—lrschedulertype: cosine
—lrschedulerwarmup_steps: 0.05
—num_epochs: 10

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 Bus Stop	Mar 100 Bus Stop	Map Do Not Enter	Mar 100 Do Not Enter	Map Do Not Stop	Mar 100 Do Not Stop	Map Do Not Turn L	Mar 100 Do Not Turn L	Map Do Not Turn R	Mar 100 Do Not Turn R	Map Do Not U Turn	Mar 100 Do Not U Turn	Map Enter Left Lane	Mar 100 Enter Left Lane	Map Green Light	Mar 100 Green Light	Map Left Right Lane	Mar 100 Left Right Lane	Map No Parking	Mar 100 No Parking	Map Parking	Mar 100 Parking	Map Ped Crossing	Mar 100 Ped Crossing	Map Ped Zebra Cross	Mar 100 Ped Zebra Cross	Map Railway Crossing	Mar 100 Railway Crossing	Map Red Light	Mar 100 Red Light	Map Stop	Mar 100 Stop	Map T Intersection L	Mar 100 T Intersection L	Map Traffic Light	Mar 100 Traffic Light	Map U Turn	Mar 100 U Turn	Map Warning	Mar 100 Warning	Map Yellow Light	Mar 100 Yellow Light
22.2876	1.0	142	16.3031	0.0001	0.0003	0.0	-1.0	0.0003	0.0001	0.0014	0.0147	0.0393	-1.0	0.0143	0.0389	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0071	0.0	0.0	0.0012	0.4357	0.0	0.0	0.0	0.0	0.0	0.0579	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0006	0.3235	0.0	0.0
10.6298	2.0	284	12.8967	0.0036	0.0072	0.0027	-1.0	0.0005	0.0037	0.1123	0.1862	0.2092	-1.0	0.0119	0.2121	0.0	0.0	0.0005	0.0824	0.0032	0.4	0.0	0.0	0.0	0.0	0.0067	0.6111	0.0261	0.56	0.0005	0.04	0.0096	0.5923	0.0	0.0	0.0	0.0	0.0144	0.7571	0.0	0.0	0.0	0.0	0.0001	0.0684	0.01	0.5133	0.0	0.0	0.0033	0.1214	0.0	0.0	0.0015	0.6471	0.0	0.0
9.1796	3.0	426	10.0319	0.021	0.0271	0.0244	-1.0	0.0084	0.0215	0.2869	0.3829	0.4119	-1.0	0.1671	0.4206	0.0	0.0	0.011	0.7647	0.19	0.8778	0.0067	0.1667	0.0009	0.125	0.022	0.7111	0.0123	0.78	0.0242	0.575	0.0485	0.9462	0.0021	0.0714	0.0	0.0	0.0103	0.8714	0.0	0.0	0.0	0.0	0.0039	0.4105	0.054	0.7	0.0026	0.1	0.0209	0.7071	0.0	0.0	0.0291	0.8	0.0017	0.0429
8.1664	4.0	568	10.4812	0.0656	0.0865	0.0802	-1.0	0.1081	0.071	0.5479	0.6705	0.6938	-1.0	0.4738	0.7013	0.0	0.0	0.0949	0.8882	0.0636	0.9222	0.0726	0.95	0.013	0.9375	0.0375	0.8222	0.0077	0.86	0.2439	0.725	0.248	0.9769	0.0458	0.8857	0.0856	0.46	0.0296	0.9	0.0379	0.6	0.0329	0.8571	0.03	0.6105	0.037	0.6933	0.0114	0.7	0.0507	0.6357	0.104	0.1	0.1279	0.8588	0.0029	0.1857
7.6975	5.0	710	10.0715	0.1155	0.134	0.1298	-1.0	0.1498	0.1175	0.6555	0.7709	0.7932	-1.0	0.6648	0.7822	0.0069	0.15	0.1771	0.9176	0.0417	0.9333	0.5852	0.95	0.0468	0.9625	0.0499	0.8333	0.0281	0.9	0.2321	0.765	0.2894	0.9846	0.1371	0.8786	0.0747	0.74	0.0535	0.9	0.1351	0.94	0.0409	0.9429	0.0632	0.7895	0.0452	0.9	0.0384	0.9	0.0573	0.6714	0.0051	0.2286	0.1829	0.9118	0.1361	0.4571
7.3315	6.0	852	10.2709	0.2027	0.2351	0.2261	-1.0	0.1476	0.2131	0.7523	0.8761	0.8919	-1.0	0.7338	0.8934	0.0072	0.7667	0.4716	0.9588	0.2372	0.9444	0.5703	0.95	0.065	0.9875	0.1324	0.9333	0.2099	0.9	0.3541	0.705	0.3525	0.9538	0.2255	0.9643	0.4336	0.86	0.1226	0.9857	0.1742	1.0	0.0449	1.0	0.0991	0.7895	0.1388	0.94	0.0922	0.9333	0.1329	0.7286	0.049	0.8286	0.3198	0.9	0.0232	0.7
7.0127	7.0	994	10.6621	0.2583	0.297	0.292	-1.0	0.2075	0.2737	0.7821	0.8987	0.9113	-1.0	0.7214	0.916	0.0088	0.8	0.5416	0.9647	0.2519	0.9444	0.3862	0.95	0.1977	0.9625	0.183	0.9333	0.0794	0.96	0.4767	0.805	0.4321	0.9615	0.4624	0.9643	0.42	0.9	0.2141	0.9786	0.4402	0.96	0.1659	1.0	0.1552	0.8211	0.0993	0.9533	0.1092	0.9556	0.0837	0.7786	0.353	0.8571	0.2944	0.8882	0.0701	0.8
7.1040	8.0	1136	10.9497	0.2791	0.3239	0.3177	-1.0	0.2893	0.2894	0.7796	0.9057	0.911	-1.0	0.8038	0.9138	0.0104	0.8167	0.7457	0.9647	0.2607	0.9556	0.6601	0.95	0.1946	0.9625	0.1462	0.9333	0.0503	0.92	0.5829	0.82	0.6416	0.9385	0.4414	0.9571	0.2341	0.84	0.2178	0.9857	0.2576	0.98	0.1035	0.9857	0.2389	0.8474	0.0761	0.9667	0.0919	0.9556	0.0841	0.7286	0.4107	0.8714	0.3392	0.9235	0.0737	0.8286
6.7829	9.0	1278	10.9346	0.3122	0.3543	0.3489	-1.0	0.2803	0.3296	0.7948	0.9115	0.9192	-1.0	0.8043	0.924	0.0184	0.8	0.6986	0.9647	0.229	0.9667	0.7064	0.95	0.2178	0.975	0.123	0.9556	0.2597	0.94	0.6141	0.835	0.6359	0.9462	0.568	0.9571	0.4532	0.9	0.2597	0.9857	0.3434	0.98	0.1308	0.9714	0.263	0.8684	0.0932	0.9533	0.1229	0.9556	0.1165	0.7357	0.3089	0.9	0.3132	0.9059	0.0813	0.8571
6.9093	10.0	1420	10.9431	0.2977	0.3348	0.3316	-1.0	0.2581	0.312	0.8002	0.914	0.9207	-1.0	0.7952	0.9256	0.0168	0.8	0.7351	0.9647	0.2201	0.9556	0.6354	0.95	0.2183	0.9625	0.1473	0.9556	0.0736	0.96	0.6003	0.85	0.6462	0.9462	0.5851	0.9357	0.4673	0.92	0.2841	0.9786	0.1496	1.0	0.1275	1.0	0.264	0.8421	0.1531	0.96	0.1283	0.9556	0.0914	0.7714	0.3491	0.8857	0.2874	0.9118	0.0724	0.8286

Framework versions

—Transformers 5.12.1
—Pytorch 2.12.1+cu130
—Datasets 5.0.0
—Tokenizers 0.22.2