rfdetr-roadsign-agree2-large-noaug

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

Loss: 14.5642
Map: 0.6232
Map 50: 0.7305
Map 75: 0.6854
Map Small: 0.5934
Map Medium: 0.3964
Map Large: 0.6258
Mar 1: 0.7795
Mar 10: 0.8595
Mar 100: 0.8674
Mar Small: 0.8
Mar Medium: 0.5161
Mar Large: 0.8801
Map Bus Stop: -1.0
Mar 100 Bus Stop: -1.0
Map Do Not Enter: 0.7149
Mar 100 Do Not Enter: 0.8333
Map Do Not Stop: 0.4899
Mar 100 Do Not Stop: 0.94
Map Do Not Turn L: 0.4096
Mar 100 Do Not Turn L: 0.875
Map Do Not Turn R: 0.6172
Mar 100 Do Not Turn R: 1.0
Map Do Not U Turn: 0.5958
Mar 100 Do Not U Turn: 0.9375
Map Enter Left Lane: 0.8422
Mar 100 Enter Left Lane: 0.94
Map Green Light: 0.5393
Mar 100 Green Light: 0.8364
Map Left Right Lane: 0.9064
Mar 100 Left Right Lane: 0.95
Map No Parking: 0.4959
Mar 100 No Parking: 0.9467
Map Parking: 0.9
Mar 100 Parking: 0.9
Map Ped Crossing: 0.5538
Mar 100 Ped Crossing: 0.9111
Map Ped Zebra Cross: 0.6284
Mar 100 Ped Zebra Cross: 0.8889
Map Railway Crossing: 0.7265
Mar 100 Railway Crossing: 0.9067
Map Red Light: 0.3009
Mar 100 Red Light: 0.6583
Map Stop: 0.8077
Mar 100 Stop: 0.8889
Map T Intersection L: 0.7483
Mar 100 T Intersection L: 0.95
Map Traffic Light: 0.2374
Mar 100 Traffic Light: 0.5357
Map U Turn: 0.824
Mar 100 U Turn: 0.85
Map Warning: 0.7575
Mar 100 Warning: 0.9
Map Yellow Light: 0.3682
Mar 100 Yellow Light: 0.7

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: 8
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: cosine
lr_scheduler_warmup_steps: 0.05
num_epochs: 30

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
175.8652	1.0	133	30.5025	0.0001	0.0005	0.0	0.0	0.0	0.0001	0.0042	0.02	0.0282	0.0	0.0	0.0293	-1.0	-1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0005	0.05	0.0005	0.2	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0278	0.0	0.0	0.0	0.0	0.0	0.0	0.0004	0.0111	0.0	0.0	0.0001	0.0286	0.0	0.0	0.0005	0.2462	0.0	0.0
18.2403	2.0	266	19.0123	0.0001	0.0005	0.0	0.0	0.0	0.0001	0.0028	0.0199	0.0639	0.0	0.0	0.065	0.0	0.0	0.0	0.0	0.0	0.0	0.0005	0.45	0.0012	0.2062	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	0.0001	0.1556	0.0	0.0	0.0	0.0286	0.0	0.0	0.0004	0.4385	0.0	0.0	-1.0	-1.0
11.9882	3.0	399	14.0584	0.0095	0.0214	0.0081	0.0	0.0133	0.0096	0.1315	0.2084	0.2425	0.0	0.0944	0.2502	0.0098	0.075	0.0144	0.1333	0.007	0.65	0.0246	0.65	0.0819	0.7875	0.0	0.0	0.001	0.2318	0.0012	0.4375	0.0201	0.5867	0.0	0.0	0.001	0.0278	0.0	0.0	0.0	0.0	0.0001	0.0833	0.0108	0.4	0.0	0.0	0.0007	0.2643	0.0	0.0	0.0183	0.5231	0.0	0.0	-1.0	-1.0
10.6541	4.0	532	12.9904	0.0361	0.0512	0.0437	0.0	0.1036	0.0308	0.4002	0.5407	0.5728	0.0	0.3228	0.5932	-1.0	-1.0	0.0231	0.8167	0.0265	0.7667	0.0141	0.65	0.0297	0.9	0.0593	0.8938	0.1033	0.8	0.2051	0.6591	0.0206	0.9125	0.1048	0.82	0.0	0.0	0.0166	0.9222	0.013	0.2444	0.0476	0.4733	0.0022	0.2833	0.0364	0.7778	0.0	0.0	0.0046	0.2714	0.0	0.0	0.0118	0.8154	0.0028	0.45
10.0810	5.0	665	12.7154	0.0756	0.0937	0.0885	0.199	0.1805	0.0708	0.6433	0.7638	0.7726	0.4	0.3567	0.7845	-1.0	-1.0	0.0299	0.8417	0.0562	0.8467	0.0117	0.85	0.0177	0.9	0.0539	0.8625	0.1181	0.9333	0.3339	0.5273	0.0284	0.9625	0.0865	0.76	0.1575	0.9667	0.1173	0.8611	0.0602	0.8778	0.0794	0.6733	0.0312	0.3333	0.1453	0.8667	0.0122	0.8	0.0746	0.3786	0.0254	0.85	0.0471	0.8615	0.0254	0.5
9.3312	6.0	798	13.2321	0.2036	0.2491	0.2331	0.3564	0.2622	0.2162	0.6857	0.7979	0.8093	0.7667	0.49	0.816	-1.0	-1.0	0.2939	0.825	0.1139	0.8467	0.0543	0.875	0.5486	0.95	0.1461	0.875	0.1612	0.8267	0.342	0.7591	0.1095	0.8875	0.0918	0.8067	0.4661	0.8333	0.25	0.8889	0.2743	0.9333	0.1008	0.68	0.0276	0.5167	0.0726	0.8556	0.0907	0.95	0.0251	0.4286	0.0412	0.8333	0.3319	0.9154	0.5294	0.7
9.1495	7.0	931	13.1461	0.2147	0.253	0.2415	0.234	0.3194	0.2027	0.7186	0.8062	0.8182	0.5	0.6072	0.8055	-1.0	-1.0	0.1581	0.85	0.2627	0.8667	0.0582	0.8	0.168	0.9	0.2786	0.9062	0.1875	0.88	0.4765	0.6773	0.498	0.9625	0.1469	0.8333	0.2666	0.8667	0.267	0.9111	0.4519	0.8889	0.2157	0.7933	0.0331	0.55	0.1995	0.9111	0.0369	0.975	0.0621	0.4214	0.1466	0.8167	0.3194	0.8538	0.06	0.7
8.4790	8.0	1064	13.2056	0.2764	0.3282	0.3195	0.3538	0.2663	0.2703	0.7383	0.8334	0.8489	0.5333	0.5822	0.856	-1.0	-1.0	0.3257	0.85	0.2309	0.88	0.4286	0.875	0.0634	0.85	0.1901	0.8813	0.5033	0.92	0.4681	0.8182	0.4805	0.9125	0.1735	0.9	0.3655	0.9	0.2534	0.9167	0.2526	0.8333	0.3817	0.8733	0.0746	0.6583	0.199	0.9222	0.1498	0.95	0.1063	0.4643	0.3653	0.85	0.41	0.9231	0.1057	0.8
8.2091	9.0	1197	13.9988	0.3464	0.4177	0.3645	0.5505	0.3893	0.339	0.7458	0.8419	0.8595	0.6667	0.535	0.8736	-1.0	-1.0	0.5625	0.8333	0.2741	0.9467	0.2515	0.825	0.1287	0.95	0.2618	0.8687	0.406	0.9133	0.5397	0.8545	0.6494	0.95	0.3169	0.8733	0.6295	0.9	0.2555	0.9167	0.3549	0.8889	0.4058	0.88	0.1446	0.6417	0.4503	0.9333	0.1999	0.95	0.0451	0.5214	0.2937	0.8667	0.331	0.8769	0.427	0.8
7.7067	10.0	1330	13.1980	0.3746	0.4449	0.4285	0.4644	0.4302	0.3603	0.7551	0.8496	0.8643	0.4667	0.5867	0.8739	-1.0	-1.0	0.7761	0.8583	0.2787	0.9467	0.1044	0.875	0.1542	0.95	0.3966	0.9187	0.4863	0.9067	0.5245	0.8545	0.4641	0.9125	0.3548	0.8467	0.7016	0.9	0.281	0.9333	0.4073	0.9111	0.3407	0.86	0.1882	0.7083	0.5989	0.9333	0.1936	0.95	0.173	0.4714	0.2184	0.85	0.4597	0.9	0.3899	0.8
7.7942	11.0	1463	13.3169	0.4275	0.5033	0.4635	0.4812	0.396	0.4158	0.7613	0.8529	0.867	0.5	0.5328	0.8839	-1.0	-1.0	0.6943	0.8667	0.3186	0.9267	0.3362	0.85	0.5591	0.95	0.3879	0.925	0.4816	0.8933	0.5049	0.8545	0.5805	0.95	0.2612	0.88	0.6655	0.8667	0.2945	0.9222	0.6501	0.9111	0.49	0.9267	0.187	0.75	0.6636	0.9556	0.1337	0.95	0.0957	0.4571	0.374	0.8667	0.4454	0.9385	0.4267	0.7
7.4175	12.0	1596	13.3963	0.444	0.5352	0.4899	0.398	0.3596	0.4459	0.7686	0.8414	0.8608	0.4	0.5528	0.8752	-1.0	-1.0	0.7109	0.8333	0.356	0.92	0.3023	0.85	0.3082	0.95	0.4229	0.925	0.6028	0.94	0.5569	0.8227	0.5646	0.9625	0.4266	0.9267	0.6715	0.9667	0.3064	0.9222	0.5944	0.8667	0.3227	0.8467	0.1796	0.7167	0.7665	0.9333	0.1864	0.9	0.2072	0.45	0.5439	0.8333	0.499	0.9	0.3519	0.75
7.1598	13.0	1729	13.7942	0.4517	0.5371	0.5142	0.216	0.3721	0.4568	0.7718	0.8556	0.8677	0.5	0.5356	0.8824	-1.0	-1.0	0.7416	0.875	0.4233	0.9333	0.2124	0.875	0.1946	0.9	0.3935	0.9125	0.6079	0.9533	0.5876	0.8591	0.629	0.925	0.4316	0.9267	0.5253	0.9333	0.3256	0.9222	0.6205	0.8556	0.4656	0.9467	0.2307	0.6417	0.8601	0.9667	0.2358	0.95	0.2125	0.4786	0.6531	0.85	0.3702	0.9	0.3127	0.75
6.6798	14.0	1862	13.4201	0.478	0.5742	0.5319	0.4096	0.3999	0.4832	0.7801	0.8463	0.8715	0.7	0.5778	0.8804	-1.0	-1.0	0.7553	0.8583	0.4124	0.92	0.2228	0.85	0.5591	0.95	0.4051	0.9187	0.7377	0.9133	0.5495	0.8409	0.4894	0.975	0.3861	0.9267	0.7091	0.8667	0.2844	0.9444	0.6247	0.9	0.3493	0.9067	0.2794	0.7583	0.8132	0.9	0.3143	0.95	0.2122	0.5286	0.651	0.85	0.4535	0.9231	0.3523	0.75
6.5150	15.0	1995	13.9702	0.4932	0.5858	0.5311	0.5307	0.3966	0.4928	0.7776	0.8523	0.868	0.5333	0.5667	0.8791	-1.0	-1.0	0.7286	0.8333	0.3094	0.9467	0.2359	0.875	0.802	0.95	0.5055	0.925	0.7438	0.92	0.5553	0.8091	0.5911	0.95	0.4546	0.9267	0.6723	0.8667	0.3933	0.9222	0.6592	0.8778	0.4483	0.92	0.1704	0.6417	0.7655	0.9222	0.1277	0.975	0.1873	0.5071	0.5457	0.8833	0.5843	0.9077	0.3842	0.8
6.7106	16.0	2128	13.9099	0.5682	0.6619	0.6179	0.4436	0.3977	0.5735	0.7846	0.8563	0.8715	0.5333	0.5483	0.884	-1.0	-1.0	0.7688	0.8417	0.4267	0.9667	0.2491	0.875	1.0	1.0	0.5737	0.9312	0.7001	0.94	0.5195	0.8545	0.671	0.9375	0.4825	0.9267	0.7091	0.8333	0.5314	0.9333	0.669	0.9222	0.6696	0.92	0.3112	0.7083	0.8422	0.9222	0.4074	0.95	0.2362	0.4929	0.6834	0.8667	0.5787	0.9077	0.3343	0.7
6.1769	17.0	2261	13.6266	0.571	0.6567	0.6082	0.4772	0.3889	0.5692	0.7814	0.8659	0.8818	0.5667	0.555	0.8943	-1.0	-1.0	0.7826	0.8667	0.3394	0.9467	0.3529	0.875	0.7525	1.0	0.5696	0.9375	0.7067	0.9267	0.5884	0.8364	0.7594	0.95	0.491	0.9467	0.7788	0.9	0.4444	0.9389	0.706	0.9111	0.6123	0.9533	0.1876	0.6583	0.8465	0.9333	0.4606	0.95	0.2078	0.5071	0.8358	0.8667	0.7334	0.9308	0.2637	0.8
5.8277	18.0	2394	14.0652	0.541	0.6346	0.5921	0.5923	0.37	0.5482	0.7904	0.8644	0.8806	0.7333	0.5628	0.888	-1.0	-1.0	0.777	0.8667	0.3714	0.9533	0.3138	0.9	0.3451	1.0	0.5069	0.9312	0.7572	0.94	0.5084	0.8409	0.8986	0.9625	0.4637	0.94	0.6349	0.8667	0.4108	0.9444	0.6685	0.8889	0.7066	0.9733	0.2258	0.6417	0.828	0.9333	0.2633	0.975	0.2743	0.5571	0.8306	0.8667	0.7016	0.9308	0.3344	0.7
5.6869	19.0	2527	14.2147	0.5985	0.7013	0.6682	0.5362	0.4035	0.601	0.7873	0.8575	0.8755	0.7333	0.5456	0.8863	-1.0	-1.0	0.7457	0.8583	0.4692	0.9333	0.428	0.825	0.835	1.0	0.5714	0.9375	0.8268	0.9333	0.5694	0.8364	0.7597	0.9625	0.3917	0.9333	0.6567	0.8667	0.5657	0.9444	0.6504	0.9	0.7221	0.94	0.3685	0.6833	0.8102	0.9111	0.5006	0.975	0.2286	0.5643	0.8366	0.8833	0.7661	0.9231	0.268	0.7
5.3519	20.0	2660	14.2657	0.6159	0.7118	0.6618	0.5194	0.3546	0.621	0.7921	0.8596	0.8743	0.8	0.5667	0.8797	-1.0	-1.0	0.763	0.85	0.547	0.9267	0.4589	0.875	0.4505	1.0	0.6086	0.95	0.7633	0.9267	0.5283	0.7818	0.9125	0.95	0.6305	0.9333	0.7788	0.9	0.6006	0.9222	0.692	0.9	0.7237	0.92	0.2432	0.65	0.8293	0.9222	0.6253	0.95	0.2305	0.5714	0.8454	0.8833	0.8007	0.9231	0.2857	0.75
5.2866	21.0	2793	14.4142	0.596	0.6951	0.6438	0.6176	0.3736	0.5922	0.7883	0.8644	0.8787	0.7333	0.5622	0.8854	-1.0	-1.0	0.7606	0.85	0.4707	0.94	0.4245	0.9	0.6168	0.95	0.5964	0.9375	0.8351	0.9267	0.5319	0.8182	0.7676	0.9375	0.5528	0.94	0.6932	0.9	0.6037	0.9333	0.7021	0.9111	0.7086	0.94	0.1489	0.6667	0.8138	0.9333	0.3882	0.975	0.2449	0.5357	0.8639	0.8833	0.7945	0.9462	0.4024	0.75
5.0301	22.0	2926	14.5795	0.6287	0.7234	0.6769	0.585	0.413	0.6265	0.787	0.8616	0.8774	0.7667	0.5983	0.8806	-1.0	-1.0	0.7488	0.85	0.4835	0.9267	0.4442	0.875	0.835	1.0	0.5555	0.9312	0.8275	0.94	0.5519	0.8455	0.9508	0.9625	0.5376	0.96	0.7222	0.8667	0.6163	0.9333	0.729	0.9111	0.7393	0.9	0.2724	0.675	0.8377	0.9111	0.412	0.925	0.2479	0.5357	0.85	0.8833	0.8439	0.9154	0.3687	0.8
5.0224	23.0	3059	14.3252	0.6502	0.7532	0.7061	0.6181	0.4193	0.6521	0.7988	0.8673	0.8793	0.7667	0.5628	0.8889	-1.0	-1.0	0.7524	0.8333	0.513	0.9333	0.4191	0.875	0.617	1.0	0.6261	0.9438	0.8617	0.94	0.5682	0.8455	0.876	0.9375	0.5756	0.94	0.9168	0.9333	0.5835	0.9222	0.7166	0.9222	0.7454	0.9	0.3735	0.6667	0.8182	0.9111	0.7816	0.95	0.2266	0.5429	0.8248	0.85	0.8393	0.9385	0.3689	0.8
4.5247	24.0	3192	14.4934	0.6336	0.7391	0.6944	0.5963	0.3985	0.635	0.7904	0.8599	0.8686	0.7333	0.5356	0.8807	-1.0	-1.0	0.7419	0.8417	0.5059	0.94	0.4243	0.875	0.6252	0.95	0.6184	0.9312	0.8529	0.9267	0.5513	0.8409	0.9085	0.95	0.4731	0.9467	0.8442	0.8667	0.6164	0.9278	0.6589	0.9111	0.7153	0.9467	0.2935	0.65	0.818	0.9	0.769	0.925	0.2407	0.5357	0.8248	0.85	0.8203	0.9077	0.3685	0.75
4.7118	25.0	3325	14.5532	0.6285	0.7342	0.6886	0.6889	0.3844	0.6321	0.7859	0.8636	0.8677	0.7667	0.5528	0.8766	-1.0	-1.0	0.7334	0.825	0.4818	0.92	0.399	0.85	0.6168	0.95	0.5872	0.9438	0.8419	0.9467	0.5277	0.8273	0.9062	0.9375	0.4751	0.9333	0.9	0.9	0.5732	0.9056	0.6219	0.8889	0.7435	0.94	0.282	0.7083	0.8276	0.9111	0.7855	0.95	0.2605	0.5571	0.8349	0.8667	0.8037	0.8923	0.3685	0.7
4.5587	26.0	3458	14.4636	0.6192	0.7277	0.6825	0.6805	0.3597	0.625	0.7791	0.8593	0.8699	0.8	0.5456	0.8802	-1.0	-1.0	0.7406	0.8417	0.4915	0.9133	0.4111	0.875	0.6172	1.0	0.5859	0.925	0.8217	0.94	0.5355	0.8455	0.9085	0.95	0.5354	0.9467	0.8442	0.8667	0.5877	0.9111	0.6176	0.8889	0.7541	0.9267	0.2947	0.65	0.8288	0.9111	0.6114	0.95	0.2612	0.5571	0.8053	0.8333	0.8042	0.9154	0.3277	0.75
4.3583	27.0	3591	14.5484	0.6238	0.7288	0.6846	0.6478	0.3935	0.6259	0.7819	0.8629	0.8721	0.7667	0.5433	0.8797	-1.0	-1.0	0.7277	0.85	0.5221	0.9333	0.3984	0.875	0.6172	1.0	0.6001	0.9312	0.8428	0.9267	0.5535	0.8318	0.9031	0.9375	0.4929	0.9533	0.9	0.9	0.5511	0.9111	0.6566	0.8889	0.73	0.9133	0.2678	0.6583	0.8202	0.9222	0.6741	0.975	0.2506	0.5286	0.8244	0.8833	0.7743	0.9231	0.3685	0.7
4.2415	28.0	3724	14.5687	0.624	0.7298	0.6853	0.5816	0.3933	0.6256	0.784	0.8626	0.8691	0.8	0.5383	0.8779	-1.0	-1.0	0.7023	0.8417	0.5058	0.92	0.4045	0.875	0.6172	1.0	0.5709	0.95	0.8459	0.9333	0.5344	0.8227	0.9062	0.9375	0.4856	0.94	0.9	0.9	0.5537	0.9056	0.6325	0.8889	0.7279	0.9133	0.278	0.675	0.8408	0.9222	0.7483	0.95	0.2415	0.55	0.8344	0.85	0.7826	0.9077	0.3684	0.7
4.1686	29.0	3857	14.5696	0.624	0.7323	0.6879	0.5732	0.395	0.6266	0.7796	0.8608	0.8728	0.7667	0.5306	0.8845	-1.0	-1.0	0.7182	0.8417	0.5064	0.9467	0.3997	0.875	0.6172	1.0	0.5745	0.9438	0.8436	0.92	0.5465	0.8273	0.9065	0.95	0.4961	0.9467	0.9	0.9	0.5624	0.9111	0.6242	0.8889	0.7217	0.9067	0.3024	0.65	0.82	0.9222	0.7485	0.975	0.2382	0.5357	0.8162	0.85	0.7696	0.9154	0.3685	0.75
4.1252	30.0	3990	14.5642	0.6232	0.7305	0.6854	0.5934	0.3964	0.6258	0.7795	0.8595	0.8674	0.8	0.5161	0.8801	-1.0	-1.0	0.7149	0.8333	0.4899	0.94	0.4096	0.875	0.6172	1.0	0.5958	0.9375	0.8422	0.94	0.5393	0.8364	0.9064	0.95	0.4959	0.9467	0.9	0.9	0.5538	0.9111	0.6284	0.8889	0.7265	0.9067	0.3009	0.6583	0.8077	0.8889	0.7483	0.95	0.2374	0.5357	0.824	0.85	0.7575	0.9	0.3682	0.7

Framework versions

Transformers 5.12.1
Pytorch 2.12.1+cu130
Datasets 5.0.0
Tokenizers 0.22.2

merve/rfdetr-roadsign-agree2-large-noaug

rfdetr-roadsign-agree2-large-noaug

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Seed this model