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koppolusameer/rfdetr-medium-basketball-playerexpanded-referee-detection

sourceHugging Faceapache-2.0updated 19d agoView on Hugging Face

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Model Card

rfdetr-medium-basketball-playerexpanded-referee-detection

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

—Loss: 17.8632
—Map: 0.6357
—Map 50: 0.8899
—Map 75: 0.7145
—Map Small: 0.5419
—Map Medium: 0.6405
—Map Large: 0.5618
—Mar 1: 0.2588
—Mar 10: 0.7011
—Mar 100: 0.7252
—Mar Small: 0.5966
—Mar Medium: 0.7565
—Mar Large: 0.693
—Map Ball-context: 0.4121
—Map Player-not-in-possession: 0.7239
—Map Referee: 0.7712

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
—trainbatchsize: 16
—evalbatchsize: 16
—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
—num_epochs: 50

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 Ball-context	Map Player-not-in-possession	Map Referee
6.7782	1.0	131	16.9941	0.4429	0.7342	0.4817	0.2469	0.4078	0.5075	0.1796	0.5717	0.6399	0.4824	0.6913	0.7263	0.1654	0.5569	0.6064
5.9324	2.0	262	16.9885	0.4611	0.8026	0.4815	0.3062	0.4626	0.4291	0.1893	0.5777	0.6186	0.447	0.6684	0.6895	0.2278	0.5767	0.5788
5.9221	3.0	393	17.0790	0.5138	0.817	0.5739	0.3695	0.5174	0.5055	0.2129	0.6144	0.6457	0.5135	0.6995	0.6662	0.2801	0.6292	0.6323
5.6476	4.0	524	16.9621	0.5196	0.8194	0.5789	0.3858	0.5145	0.4487	0.2076	0.6161	0.6489	0.4817	0.698	0.5732	0.2662	0.6274	0.6651
5.3295	5.0	655	17.3241	0.5073	0.8067	0.5632	0.3867	0.5017	0.5022	0.2095	0.6072	0.6476	0.535	0.6903	0.6136	0.2651	0.6156	0.6413
5.4793	6.0	786	17.5006	0.5183	0.8179	0.5736	0.43	0.5186	0.5565	0.2089	0.6131	0.6531	0.5856	0.6951	0.6272	0.2717	0.6284	0.6549
5.1309	7.0	917	17.4162	0.524	0.826	0.5733	0.3295	0.5473	0.417	0.2187	0.6109	0.6451	0.5165	0.695	0.6456	0.2822	0.6281	0.6615
5.1459	8.0	1048	17.7630	0.5051	0.8091	0.5603	0.3283	0.5124	0.5159	0.2125	0.5993	0.6385	0.4795	0.6798	0.6303	0.2736	0.6053	0.6366
4.9913	9.0	1179	18.3327	0.5314	0.8403	0.5973	0.4636	0.5427	0.4783	0.2213	0.6174	0.6437	0.5981	0.6811	0.5684	0.3021	0.6279	0.6643
5.1497	10.0	1310	17.2498	0.521	0.8254	0.5758	0.3812	0.5422	0.4978	0.2093	0.6129	0.6484	0.4923	0.6915	0.6355	0.2742	0.6387	0.6501
4.8780	11.0	1441	17.6133	0.5488	0.8464	0.6029	0.4589	0.565	0.4412	0.232	0.6293	0.6608	0.5725	0.7029	0.6088	0.3272	0.6309	0.6883
5.0845	12.0	1572	17.2694	0.5437	0.8572	0.5977	0.4126	0.5497	0.4628	0.2232	0.6281	0.6607	0.4996	0.7066	0.6754	0.3241	0.6402	0.667
4.8094	13.0	1703	16.9651	0.5559	0.8615	0.6227	0.3591	0.5872	0.4924	0.2263	0.6367	0.6743	0.4758	0.7226	0.6338	0.3284	0.6615	0.6779
4.7197	14.0	1834	17.3401	0.553	0.8474	0.6126	0.4627	0.5585	0.4688	0.2264	0.632	0.6682	0.5661	0.7091	0.5991	0.3199	0.6489	0.6902
4.6574	15.0	1965	17.0835	0.5663	0.8557	0.6343	0.424	0.5902	0.4802	0.2322	0.6379	0.6733	0.5338	0.7201	0.6689	0.3336	0.6652	0.7
4.5045	16.0	2096	17.6639	0.5664	0.8505	0.6352	0.4321	0.5825	0.5077	0.2337	0.6405	0.6682	0.5609	0.7143	0.6579	0.3396	0.6658	0.6937
4.6084	17.0	2227	18.0393	0.557	0.8529	0.6163	0.4822	0.5673	0.4864	0.229	0.6392	0.6729	0.5441	0.717	0.6469	0.307	0.6608	0.7031
4.3929	18.0	2358	17.7663	0.571	0.8512	0.6369	0.4286	0.5759	0.5227	0.2361	0.6491	0.6866	0.5196	0.7247	0.6526	0.3245	0.6774	0.711
4.3366	19.0	2489	17.3066	0.5652	0.8586	0.6374	0.4339	0.5746	0.518	0.2322	0.6487	0.6793	0.548	0.7164	0.6934	0.3427	0.6626	0.6902
4.4149	20.0	2620	17.6257	0.5774	0.863	0.6533	0.4662	0.5922	0.5585	0.2396	0.6566	0.6858	0.5806	0.727	0.6434	0.3566	0.6768	0.6989
4.2230	21.0	2751	16.9326	0.5869	0.8605	0.6692	0.5022	0.5999	0.5402	0.2364	0.662	0.6959	0.5678	0.7401	0.7031	0.3545	0.6759	0.7303
4.1753	22.0	2882	17.5102	0.592	0.8618	0.6754	0.4994	0.5961	0.5441	0.2469	0.6628	0.6966	0.6287	0.7339	0.6338	0.3596	0.6807	0.7357
4.0219	23.0	3013	17.4269	0.587	0.8609	0.652	0.473	0.593	0.5397	0.2379	0.6619	0.6879	0.541	0.7265	0.643	0.3465	0.6844	0.73
4.0634	24.0	3144	17.6983	0.5891	0.8644	0.6598	0.4845	0.6085	0.4752	0.2425	0.6543	0.6894	0.5648	0.7306	0.6746	0.3569	0.683	0.7274
4.0055	25.0	3275	17.4897	0.5861	0.8653	0.6549	0.4643	0.5924	0.5233	0.2446	0.6606	0.6884	0.5278	0.7213	0.6759	0.3547	0.6801	0.7234
3.9803	26.0	3406	17.3909	0.5902	0.8546	0.6526	0.517	0.5969	0.4668	0.2432	0.6702	0.7006	0.576	0.7393	0.6627	0.3425	0.6885	0.7398
3.8023	27.0	3537	17.6352	0.588	0.8476	0.6705	0.4876	0.584	0.5273	0.2371	0.6698	0.6995	0.5406	0.7347	0.6368	0.3322	0.6894	0.7424
3.8347	28.0	3668	18.1386	0.6031	0.8689	0.6847	0.4822	0.6041	0.4794	0.2456	0.6747	0.7022	0.5357	0.7334	0.6991	0.3715	0.6931	0.7448
3.8423	29.0	3799	17.9020	0.6127	0.8744	0.6962	0.4996	0.6245	0.5168	0.2479	0.6748	0.7074	0.5656	0.747	0.6491	0.3848	0.7018	0.7516
3.6787	30.0	3930	17.7047	0.6064	0.8722	0.6885	0.5281	0.6107	0.5948	0.2494	0.6808	0.7065	0.608	0.7452	0.6461	0.385	0.6976	0.7365
3.6963	31.0	4061	17.9157	0.6115	0.8745	0.6912	0.4915	0.6183	0.483	0.2459	0.6806	0.7116	0.5686	0.7512	0.6658	0.3746	0.7082	0.7518
3.5860	32.0	4192	17.9067	0.6007	0.8569	0.6777	0.5296	0.6064	0.5323	0.2394	0.6774	0.7137	0.6049	0.7546	0.6645	0.3426	0.704	0.7555
3.5189	33.0	4323	18.0097	0.6203	0.8799	0.7033	0.5372	0.6352	0.5021	0.2525	0.6875	0.7146	0.6033	0.7504	0.6632	0.4033	0.7051	0.7526
3.4391	34.0	4454	17.8509	0.6188	0.8782	0.6934	0.5421	0.6271	0.5514	0.2505	0.6872	0.7146	0.6012	0.7485	0.6908	0.3891	0.7074	0.7599
3.3732	35.0	4585	17.7785	0.6185	0.8783	0.6991	0.5011	0.6228	0.5692	0.2482	0.6881	0.7176	0.5631	0.7519	0.7101	0.38	0.7143	0.7612
3.3652	36.0	4716	17.6646	0.6175	0.878	0.6982	0.5174	0.6195	0.5662	0.2508	0.6861	0.7154	0.5808	0.7471	0.7009	0.3894	0.7133	0.7497
3.4803	37.0	4847	17.7310	0.6236	0.8836	0.7093	0.4922	0.635	0.5574	0.2602	0.6905	0.7177	0.5704	0.752	0.6618	0.404	0.7101	0.7568
3.2722	38.0	4978	17.7508	0.628	0.8837	0.7133	0.5244	0.6324	0.5711	0.2579	0.6972	0.7234	0.5877	0.7555	0.6846	0.406	0.715	0.7629
3.2550	39.0	5109	17.6792	0.6351	0.8861	0.7264	0.5355	0.6432	0.5557	0.2565	0.7021	0.7264	0.5996	0.7595	0.6947	0.4168	0.7186	0.77
3.2402	40.0	5240	17.7298	0.6315	0.8823	0.717	0.5433	0.6373	0.5704	0.2567	0.6968	0.7275	0.6155	0.7608	0.6978	0.4156	0.7166	0.7624
3.1442	41.0	5371	17.7419	0.6344	0.8854	0.7121	0.5494	0.6389	0.5502	0.2623	0.7009	0.728	0.617	0.7603	0.6627	0.415	0.7211	0.7672
3.1479	42.0	5502	17.8540	0.6385	0.8916	0.7253	0.5529	0.6418	0.5203	0.2619	0.7021	0.7289	0.6173	0.76	0.657	0.421	0.7216	0.773
3.0678	43.0	5633	17.7972	0.6396	0.893	0.7188	0.5426	0.6458	0.5611	0.2608	0.7015	0.7238	0.5966	0.7558	0.6583	0.4242	0.7216	0.773
3.1587	44.0	5764	17.8076	0.6381	0.8902	0.7169	0.5515	0.64	0.5618	0.26	0.7034	0.7259	0.6118	0.7568	0.6794	0.4186	0.7225	0.7732
3.0502	45.0	5895	17.8509	0.6377	0.891	0.7179	0.5427	0.6415	0.5792	0.2597	0.7012	0.7272	0.6027	0.7565	0.6649	0.4169	0.7232	0.773
3.0924	46.0	6026	17.8412	0.6374	0.89	0.7138	0.5429	0.6428	0.5631	0.2593	0.6997	0.7279	0.6039	0.7571	0.6846	0.4156	0.7245	0.772
3.0594	47.0	6157	17.8785	0.6356	0.8877	0.7132	0.5403	0.6406	0.5715	0.2587	0.7001	0.7238	0.5966	0.7547	0.686	0.4114	0.7252	0.7702
3.0586	48.0	6288	17.8621	0.6355	0.8895	0.7141	0.5413	0.6405	0.5513	0.2585	0.6981	0.7253	0.5969	0.758	0.6737	0.4118	0.7245	0.7703
3.0605	49.0	6419	17.8728	0.6365	0.8899	0.7147	0.5429	0.6403	0.5589	0.2595	0.7014	0.7259	0.6011	0.7549	0.6846	0.414	0.7244	0.7712
3.0423	50.0	6550	17.8628	0.6359	0.89	0.7146	0.5417	0.6407	0.5618	0.2587	0.7009	0.7252	0.5969	0.7561	0.693	0.4121	0.7242	0.7712

Framework versions

—Transformers 5.16.1
—Pytorch 2.11.0+cu128
—Datasets 4.0.0
—Tokenizers 0.23.1