law-game-replace-finetune

anastasispk/law-game-replace-finetune

law-game-replace-finetune is a object detection model from anastasispk. 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 1, 2024
Updated: Aug 1, 2024
SHA: a4e2c0ba

Base models

PekingU/rtdetr_r50vd_coco_o365

Model card

From the Hugging Face model README

law-game-replace-finetune

This model is a fine-tuned version of PekingU/rtdetr_r50vd_coco_o365 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 5.6852
Map: 0.8547
Map 50: 0.9219
Map 75: 0.8855
Map Small: 0.6003
Map Medium: 0.6465
Map Large: 0.9074
Mar 1: 0.652
Mar 10: 0.9364
Mar 100: 0.9452
Mar Small: 0.779
Mar Medium: 0.924
Mar Large: 0.9818
Map Evidence: -1.0
Mar 100 Evidence: -1.0
Map Ambulance: 1.0
Mar 100 Ambulance: 1.0
Map Artificial Target: 0.8084
Mar 100 Artificial Target: 0.8727
Map Cartridge: 0.9022
Mar 100 Cartridge: 0.9681
Map Gun: 0.7068
Mar 100 Gun: 0.9667
Map Knife: 0.7732
Mar 100 Knife: 0.9111
Map Police: 0.9573
Mar 100 Police: 0.9818
Map Traffic: 0.835
Mar 100 Traffic: 0.9162

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 300
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 Evidence	Mar 100 Evidence	Map Ambulance	Mar 100 Ambulance	Map Artificial Target	Mar 100 Artificial Target	Map Cartridge	Mar 100 Cartridge	Map Gun	Mar 100 Gun	Map Knife	Mar 100 Knife	Map Police	Mar 100 Police	Map Traffic	Mar 100 Traffic
No log	1.0	35	134.6829	0.0007	0.0015	0.0001	0.0	0.0001	0.0025	0.0014	0.0168	0.0462	0.0	0.0686	0.0457	-1.0	-1.0	0.0	0.0	0.0	0.0023	0.0033	0.0203	0.0	0.0407	0.0001	0.1667	0.0009	0.0909	0.0004	0.0027
No log	2.0	70	65.3809	0.0021	0.0028	0.0022	0.0001	0.0003	0.0074	0.0229	0.0958	0.167	0.095	0.3103	0.1895	-1.0	-1.0	0.0	0.0	0.0	0.0114	0.0	0.0203	0.0002	0.2444	0.0007	0.4185	0.007	0.3364	0.0064	0.1378
No log	3.0	105	35.8052	0.0174	0.0218	0.0181	0.0018	0.0208	0.0403	0.1026	0.3488	0.4766	0.2068	0.3434	0.5788	-1.0	-1.0	0.002	0.6	0.0299	0.5614	0.0465	0.4087	0.0025	0.4889	0.0087	0.6963	0.0043	0.3727	0.0275	0.2081
No log	4.0	140	25.0458	0.1381	0.1523	0.1431	0.0303	0.1563	0.182	0.3056	0.7303	0.8222	0.3066	0.7579	0.9116	-1.0	-1.0	0.0486	0.99	0.1396	0.8114	0.5183	0.9478	0.0069	0.6519	0.1362	0.8556	0.0466	0.9909	0.0704	0.5081
No log	5.0	175	17.7820	0.3449	0.3761	0.3616	0.1626	0.3378	0.4356	0.4732	0.8209	0.8887	0.5946	0.834	0.9595	-1.0	-1.0	0.049	0.99	0.5783	0.8307	0.7758	0.9507	0.0242	0.8519	0.3644	0.8889	0.4966	0.9909	0.1259	0.7176
No log	6.0	210	12.9410	0.5642	0.6087	0.5938	0.2533	0.4341	0.6233	0.5662	0.8824	0.9137	0.6323	0.8828	0.9676	-1.0	-1.0	0.522	0.99	0.5584	0.8205	0.8377	0.9754	0.2365	0.8889	0.6276	0.9	0.907	0.9818	0.2599	0.8392
No log	7.0	245	10.9532	0.621	0.6648	0.6501	0.2326	0.5144	0.7328	0.557	0.8817	0.9294	0.7018	0.9104	0.9762	-1.0	-1.0	0.8543	0.99	0.7325	0.8534	0.8209	0.9783	0.1195	0.9148	0.4129	0.9222	0.8795	0.9727	0.527	0.8743
No log	8.0	280	10.0540	0.5983	0.6382	0.6263	0.2675	0.4634	0.7109	0.5338	0.8619	0.8908	0.7047	0.8926	0.9389	-1.0	-1.0	0.6275	0.99	0.7514	0.8477	0.8526	0.9739	0.3547	0.937	0.5777	0.9185	0.5453	0.7091	0.4788	0.8595
No log	9.0	315	9.1369	0.7135	0.7584	0.7387	0.3085	0.5685	0.8728	0.602	0.9018	0.9292	0.708	0.7784	0.9823	-1.0	-1.0	0.9209	0.99	0.7616	0.833	0.8367	0.9681	0.258	0.9037	0.7433	0.9296	0.9341	0.9909	0.54	0.8892
No log	10.0	350	8.3330	0.7455	0.7925	0.7791	0.3892	0.5906	0.8393	0.6105	0.9109	0.9418	0.7521	0.8131	0.9867	-1.0	-1.0	0.8772	0.99	0.7901	0.8602	0.8873	0.9797	0.4403	0.9407	0.6274	0.9259	0.884	0.9909	0.7124	0.9054
No log	11.0	385	7.8064	0.7386	0.7829	0.7659	0.386	0.5855	0.8299	0.598	0.9136	0.9447	0.7716	0.8992	0.9875	-1.0	-1.0	0.9646	0.99	0.797	0.8773	0.8289	0.9739	0.2469	0.9593	0.6911	0.9148	0.9411	0.9909	0.7008	0.9068
No log	12.0	420	7.3854	0.7433	0.7883	0.7675	0.4603	0.5849	0.8471	0.6029	0.9147	0.9389	0.7745	0.8155	0.9831	-1.0	-1.0	0.9646	0.99	0.8199	0.8602	0.7835	0.9754	0.2672	0.9222	0.6356	0.9296	0.9685	0.9909	0.7639	0.9041
No log	13.0	455	7.1834	0.7809	0.8401	0.7988	0.4502	0.6114	0.8633	0.6232	0.9163	0.9319	0.7806	0.814	0.9751	-1.0	-1.0	0.9495	0.99	0.7535	0.8625	0.8276	0.9725	0.5165	0.8963	0.7709	0.9259	0.8929	0.9818	0.7556	0.8946
No log	14.0	490	6.9868	0.7827	0.8428	0.8038	0.4806	0.6204	0.8808	0.6146	0.918	0.9335	0.7759	0.7932	0.9763	-1.0	-1.0	0.8188	0.99	0.8202	0.8727	0.8257	0.9551	0.5485	0.9074	0.7324	0.9222	0.9589	0.9909	0.7743	0.8959
32.4583	15.0	525	6.9190	0.7805	0.8338	0.8066	0.4936	0.595	0.8772	0.6148	0.9272	0.9467	0.7756	0.9095	0.9864	-1.0	-1.0	0.912	0.99	0.7913	0.8557	0.8613	0.9855	0.5283	0.963	0.6932	0.9296	0.8962	0.9909	0.7809	0.9122
32.4583	16.0	560	7.0608	0.7653	0.8279	0.7837	0.5397	0.5975	0.838	0.6004	0.9049	0.9226	0.7743	0.8751	0.9682	-1.0	-1.0	0.9569	0.99	0.7921	0.8455	0.7774	0.9174	0.4303	0.9	0.6478	0.9185	0.9515	0.9909	0.8008	0.8959
32.4583	17.0	595	6.5305	0.7648	0.8275	0.7858	0.4759	0.6282	0.866	0.6017	0.919	0.9327	0.7467	0.8837	0.977	-1.0	-1.0	0.982	0.99	0.8007	0.8648	0.8692	0.971	0.2549	0.9296	0.7184	0.9	0.9133	0.9818	0.8148	0.8919
32.4583	18.0	630	6.3597	0.7757	0.837	0.8076	0.5064	0.6482	0.863	0.5974	0.9229	0.9362	0.7693	0.8368	0.9779	-1.0	-1.0	0.8771	1.0	0.8099	0.867	0.9032	0.9696	0.2876	0.9222	0.7655	0.9074	0.9522	0.9818	0.8346	0.9054
32.4583	19.0	665	6.2977	0.8016	0.8679	0.8317	0.5793	0.6589	0.8646	0.6006	0.9256	0.9403	0.7879	0.9265	0.9749	-1.0	-1.0	0.9534	0.99	0.8131	0.8739	0.9071	0.9725	0.4297	0.9407	0.7494	0.9185	0.9567	0.9909	0.8015	0.8959
32.4583	20.0	700	6.2690	0.7843	0.8443	0.8135	0.5068	0.6505	0.887	0.6166	0.9212	0.9362	0.7759	0.8952	0.9767	-1.0	-1.0	0.9725	0.99	0.8173	0.8739	0.8936	0.9812	0.3364	0.9296	0.7669	0.9037	0.9347	0.9818	0.7686	0.8932
32.4583	21.0	735	6.3902	0.8137	0.8806	0.8417	0.7055	0.6578	0.8776	0.6087	0.9276	0.9445	0.7868	0.9097	0.9828	-1.0	-1.0	0.9807	0.99	0.8096	0.8739	0.9099	0.9696	0.5614	0.9741	0.6762	0.9074	0.9398	0.9909	0.8186	0.9054
32.4583	22.0	770	6.5328	0.8196	0.8927	0.8492	0.5932	0.626	0.876	0.6229	0.9181	0.9309	0.785	0.8935	0.9673	-1.0	-1.0	0.9881	0.99	0.8162	0.8705	0.8924	0.9638	0.6492	0.9333	0.7485	0.8704	0.8867	0.9818	0.7563	0.9068
32.4583	23.0	805	6.2433	0.8291	0.8944	0.8509	0.5805	0.6343	0.9025	0.64	0.9191	0.9392	0.8098	0.8845	0.981	-1.0	-1.0	1.0	1.0	0.8052	0.8705	0.9029	0.9623	0.5827	0.9333	0.7635	0.9222	0.9357	0.9818	0.8135	0.9041
32.4583	24.0	840	6.1554	0.8171	0.885	0.8449	0.6088	0.6328	0.8923	0.6174	0.9203	0.9316	0.7746	0.782	0.976	-1.0	-1.0	1.0	1.0	0.8049	0.8727	0.878	0.9667	0.5197	0.9148	0.75	0.8889	0.9508	0.9818	0.8159	0.8959
32.4583	25.0	875	5.9349	0.8258	0.8844	0.8498	0.6153	0.6481	0.8945	0.6112	0.9268	0.9361	0.7883	0.7972	0.9813	-1.0	-1.0	1.0	1.0	0.8164	0.8795	0.9086	0.9565	0.4921	0.9185	0.7741	0.9185	0.9465	0.9727	0.8429	0.9068
32.4583	26.0	910	6.3160	0.7895	0.8497	0.8183	0.5915	0.6343	0.8686	0.6264	0.9223	0.9318	0.7793	0.8842	0.9716	-1.0	-1.0	0.9497	0.99	0.7948	0.867	0.859	0.9493	0.3445	0.9333	0.7677	0.9	0.968	0.9818	0.8428	0.9014
32.4583	27.0	945	6.4135	0.8095	0.8772	0.838	0.5667	0.6294	0.876	0.6148	0.9118	0.9303	0.7603	0.876	0.9693	-1.0	-1.0	0.9317	0.98	0.8026	0.8648	0.8146	0.9246	0.5762	0.9481	0.7626	0.9111	0.9675	0.9818	0.8115	0.9014
32.4583	28.0	980	5.8669	0.8351	0.8972	0.8582	0.6038	0.6358	0.8918	0.6464	0.928	0.9365	0.795	0.8915	0.9783	-1.0	-1.0	0.9752	0.99	0.821	0.8739	0.8749	0.9754	0.6426	0.9444	0.7537	0.8741	0.9634	0.9909	0.8152	0.9068
5.1898	29.0	1015	5.9247	0.86	0.9246	0.882	0.6164	0.6296	0.9322	0.6408	0.9206	0.9326	0.7759	0.8898	0.9781	-1.0	-1.0	0.991	1.0	0.8174	0.8636	0.8344	0.9174	0.7097	0.9333	0.8459	0.9259	0.9812	0.9909	0.8404	0.8973
5.1898	30.0	1050	5.9808	0.8348	0.9006	0.8552	0.5928	0.6299	0.8899	0.6409	0.9203	0.928	0.7853	0.7907	0.9711	-1.0	-1.0	0.9901	0.99	0.8064	0.8693	0.8471	0.9449	0.7043	0.9222	0.7611	0.9	0.9621	0.9818	0.7727	0.8878
5.1898	31.0	1085	5.9738	0.8511	0.9076	0.8774	0.5968	0.6397	0.9095	0.644	0.9194	0.9335	0.7835	0.8017	0.9779	-1.0	-1.0	0.9835	1.0	0.8134	0.8739	0.8661	0.9362	0.744	0.9222	0.7586	0.9296	0.9647	0.9727	0.8277	0.9
5.1898	32.0	1120	6.0519	0.8567	0.9245	0.8833	0.6084	0.6568	0.9083	0.6565	0.9215	0.9332	0.7877	0.8841	0.9733	-1.0	-1.0	0.982	0.99	0.8148	0.8682	0.8808	0.9681	0.7649	0.9333	0.7794	0.8926	0.9557	0.9818	0.8196	0.8986
5.1898	33.0	1155	5.8607	0.8556	0.9226	0.8835	0.6277	0.6905	0.9001	0.6521	0.926	0.9366	0.7708	0.9035	0.9755	-1.0	-1.0	1.0	1.0	0.7983	0.8693	0.8764	0.9609	0.7527	0.9444	0.7659	0.8889	0.9675	0.9818	0.8285	0.9108
5.1898	34.0	1190	5.7650	0.851	0.9163	0.8812	0.5894	0.6515	0.9045	0.6564	0.9253	0.9367	0.7932	0.8781	0.9762	-1.0	-1.0	1.0	1.0	0.7983	0.875	0.8831	0.9609	0.667	0.9444	0.7993	0.8852	0.9675	0.9818	0.842	0.9095
5.1898	35.0	1225	5.6566	0.8525	0.9147	0.8784	0.5964	0.6244	0.905	0.6486	0.9316	0.9414	0.7726	0.9147	0.9757	-1.0	-1.0	0.9772	1.0	0.8076	0.8682	0.9067	0.9667	0.6843	0.9407	0.7884	0.9074	0.9812	0.9909	0.8225	0.9162
5.1898	36.0	1260	5.7578	0.8626	0.9252	0.89	0.6101	0.6392	0.9241	0.6555	0.9323	0.9426	0.785	0.9145	0.9808	-1.0	-1.0	0.9835	1.0	0.8056	0.8636	0.8808	0.9696	0.7216	0.963	0.8373	0.9074	0.9812	0.9909	0.8284	0.9041
5.1898	37.0	1295	5.7752	0.8529	0.9132	0.8854	0.6004	0.6418	0.9072	0.6458	0.9251	0.9412	0.7632	0.9092	0.9834	-1.0	-1.0	0.9772	1.0	0.8062	0.8693	0.8795	0.9594	0.7218	0.9407	0.7752	0.9222	0.9652	0.9818	0.8453	0.9149
5.1898	38.0	1330	5.8527	0.854	0.9169	0.8842	0.6171	0.6414	0.9136	0.6539	0.9288	0.9456	0.7921	0.9069	0.9876	-1.0	-1.0	0.991	1.0	0.8115	0.8773	0.8773	0.9652	0.6804	0.9667	0.8167	0.9185	0.9651	0.9818	0.8358	0.9095
5.1898	39.0	1365	5.6796	0.864	0.9314	0.8903	0.6112	0.6373	0.9218	0.6476	0.9308	0.9413	0.7787	0.9145	0.9782	-1.0	-1.0	1.0	1.0	0.8099	0.8705	0.9009	0.9652	0.706	0.9556	0.8127	0.8963	0.9812	0.9909	0.8375	0.9108
5.1898	40.0	1400	5.6425	0.8536	0.9205	0.8835	0.6029	0.6507	0.9146	0.6521	0.9329	0.9418	0.7882	0.9185	0.9792	-1.0	-1.0	0.9772	1.0	0.8058	0.8716	0.909	0.9696	0.6723	0.9593	0.7884	0.9074	0.9647	0.9727	0.8578	0.9122
5.1898	41.0	1435	5.6851	0.8526	0.9164	0.8808	0.6038	0.6471	0.916	0.6569	0.9325	0.9399	0.7945	0.9122	0.9793	-1.0	-1.0	1.0	1.0	0.8085	0.875	0.923	0.9754	0.6399	0.9407	0.7996	0.9037	0.9738	0.9818	0.8236	0.9027
5.1898	42.0	1470	5.6092	0.864	0.9291	0.893	0.6087	0.6473	0.9309	0.652	0.9334	0.9418	0.7832	0.9139	0.9805	-1.0	-1.0	1.0	1.0	0.8058	0.8705	0.9203	0.9681	0.6728	0.9667	0.8363	0.9	0.9647	0.9727	0.8484	0.9149
4.0823	43.0	1505	5.4824	0.8709	0.9372	0.8972	0.6011	0.6472	0.937	0.6562	0.9342	0.9434	0.7777	0.9143	0.9847	-1.0	-1.0	1.0	1.0	0.8119	0.8705	0.9112	0.9652	0.721	0.963	0.8411	0.9222	0.9652	0.9818	0.846	0.9014
4.0823	44.0	1540	5.5914	0.8642	0.9316	0.8912	0.6061	0.6487	0.9302	0.6586	0.9353	0.9424	0.7779	0.9139	0.9826	-1.0	-1.0	0.991	1.0	0.8078	0.8693	0.9284	0.971	0.6971	0.9667	0.8299	0.9037	0.9654	0.9818	0.8299	0.9041
4.0823	45.0	1575	5.6331	0.86	0.9296	0.8902	0.6114	0.6418	0.9152	0.6456	0.9336	0.9419	0.7856	0.9124	0.9809	-1.0	-1.0	1.0	1.0	0.8105	0.8773	0.9199	0.9696	0.7093	0.9593	0.7953	0.9	0.9653	0.9818	0.82	0.9054
4.0823	46.0	1610	5.6049	0.8607	0.9295	0.889	0.6164	0.6419	0.9181	0.6484	0.9316	0.9404	0.7568	0.9149	0.9799	-1.0	-1.0	0.991	1.0	0.8076	0.8716	0.9103	0.971	0.7084	0.9556	0.8046	0.9	0.9647	0.9727	0.838	0.9122
4.0823	47.0	1645	5.6549	0.8492	0.9148	0.8762	0.6114	0.6449	0.9051	0.6431	0.9325	0.9427	0.7934	0.9172	0.9801	-1.0	-1.0	0.9835	1.0	0.8064	0.8773	0.9207	0.9667	0.6572	0.963	0.7851	0.9074	0.9647	0.9727	0.8268	0.9122
4.0823	48.0	1680	5.5983	0.858	0.926	0.8891	0.6136	0.6419	0.9136	0.6499	0.9324	0.9438	0.7845	0.9192	0.9812	-1.0	-1.0	0.9835	1.0	0.8059	0.8739	0.9212	0.971	0.7215	0.963	0.773	0.9037	0.9589	0.9818	0.8419	0.9135
4.0823	49.0	1715	5.6368	0.8556	0.9223	0.8844	0.6091	0.6486	0.9069	0.6488	0.9349	0.9438	0.7895	0.9236	0.979	-1.0	-1.0	0.991	1.0	0.81	0.8739	0.9161	0.9696	0.7073	0.963	0.7632	0.9074	0.9577	0.9727	0.8439	0.9203
4.0823	50.0	1750	5.6852	0.8547	0.9219	0.8855	0.6003	0.6465	0.9074	0.652	0.9364	0.9452	0.779	0.924	0.9818	-1.0	-1.0	1.0	1.0	0.8084	0.8727	0.9022	0.9681	0.7068	0.9667	0.7732	0.9111	0.9573	0.9818	0.835	0.9162

Framework versions

Transformers 4.44.0.dev0
Pytorch 2.3.1+cu121
Tokenizers 0.19.1

Task: Object Detection
Library: transformers
Type: rt_detr
License: apache-2.0
Created: Aug 1, 2024
Updated: Aug 1, 2024