Yolo_test

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

• Loss: 1.3290
• Map: 0.1338
• Map 50: 0.2829
• Map 75: 0.1119
• Map Small: 0.0653
• Map Medium: 0.1961
• Map Large: -1.0
• Mar 1: 0.1889
• Mar 10: 0.3333
• Mar 100: 0.3815
• Mar Small: 0.38
• Mar Medium: 0.3824
• Mar Large: -1.0
• Map Background : -1.0
• Mar 100 Background : -1.0
• Map Score: 0.1338
• Mar 100 Score: 0.3815

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• 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 Background	Mar 100 Background	Map Score	Mar 100 Score
No log	1.0	93	1.3889	0.0097	0.0437	0.0002	0.0124	0.0108	-1.0	0.0259	0.1444	0.1852	0.19	0.1824	-1.0	-1.0	-1.0	0.0097	0.1852
No log	2.0	186	1.3371	0.0379	0.1162	0.0014	0.0348	0.0454	-1.0	0.0407	0.2037	0.2185	0.2	0.2294	-1.0	-1.0	-1.0	0.0379	0.2185
No log	3.0	279	1.6085	0.0058	0.0317	0.0014	0.0017	0.0102	-1.0	0.0222	0.1037	0.1037	0.02	0.1529	-1.0	-1.0	-1.0	0.0058	0.1037
No log	4.0	372	1.2737	0.0119	0.0385	0.0021	0.0285	0.0056	-1.0	0.0185	0.2074	0.2519	0.37	0.1824	-1.0	-1.0	-1.0	0.0119	0.2519
No log	5.0	465	1.0391	0.0218	0.0505	0.0203	0.0556	0.0103	-1.0	0.0296	0.3148	0.437	0.73	0.2647	-1.0	-1.0	-1.0	0.0218	0.437
1.0243	6.0	558	1.2415	0.0105	0.0342	0.0022	0.0126	0.0123	-1.0	0.0185	0.1444	0.2926	0.27	0.3059	-1.0	-1.0	-1.0	0.0105	0.2926
1.0243	7.0	651	1.0791	0.0244	0.0722	0.0063	0.0412	0.0226	-1.0	0.0481	0.3111	0.3741	0.48	0.3118	-1.0	-1.0	-1.0	0.0244	0.3741
1.0243	8.0	744	1.1443	0.0388	0.1407	0.0012	0.0482	0.0422	-1.0	0.0667	0.2815	0.3259	0.34	0.3176	-1.0	-1.0	-1.0	0.0388	0.3259
1.0243	9.0	837	1.1221	0.0366	0.1054	0.0035	0.0414	0.0372	-1.0	0.0407	0.2963	0.3815	0.44	0.3471	-1.0	-1.0	-1.0	0.0366	0.3815
1.0243	10.0	930	1.1264	0.0445	0.1488	0.009	0.0899	0.0362	-1.0	0.0963	0.3259	0.4074	0.48	0.3647	-1.0	-1.0	-1.0	0.0445	0.4074
0.6487	11.0	1023	1.1333	0.0471	0.1532	0.0118	0.0442	0.0676	-1.0	0.0593	0.2778	0.2889	0.24	0.3176	-1.0	-1.0	-1.0	0.0471	0.2889
0.6487	12.0	1116	1.2594	0.0448	0.1664	0.0006	0.0413	0.0583	-1.0	0.0667	0.2444	0.263	0.26	0.2647	-1.0	-1.0	-1.0	0.0448	0.263
0.6487	13.0	1209	1.1627	0.033	0.1218	0.003	0.0487	0.0377	-1.0	0.0333	0.3	0.3148	0.38	0.2765	-1.0	-1.0	-1.0	0.033	0.3148
0.6487	14.0	1302	1.2219	0.0669	0.2662	0.014	0.0835	0.0711	-1.0	0.1148	0.2889	0.3148	0.3	0.3235	-1.0	-1.0	-1.0	0.0669	0.3148
0.6487	15.0	1395	1.1355	0.0994	0.2971	0.0248	0.1038	0.1244	-1.0	0.1519	0.337	0.3741	0.35	0.3882	-1.0	-1.0	-1.0	0.0994	0.3741
0.6487	16.0	1488	1.1675	0.1154	0.3476	0.026	0.1273	0.1285	-1.0	0.1667	0.3	0.3444	0.34	0.3471	-1.0	-1.0	-1.0	0.1154	0.3444
0.4946	17.0	1581	1.2258	0.0976	0.2925	0.0282	0.0668	0.1497	-1.0	0.1444	0.3148	0.3704	0.33	0.3941	-1.0	-1.0	-1.0	0.0976	0.3704
0.4946	18.0	1674	1.2367	0.1138	0.3025	0.045	0.0959	0.1453	-1.0	0.1778	0.3481	0.4	0.43	0.3824	-1.0	-1.0	-1.0	0.1138	0.4
0.4946	19.0	1767	1.2897	0.1208	0.3045	0.0764	0.0784	0.1481	-1.0	0.1778	0.3296	0.3704	0.39	0.3588	-1.0	-1.0	-1.0	0.1208	0.3704
0.4946	20.0	1860	1.2484	0.1321	0.3143	0.0969	0.092	0.1805	-1.0	0.1926	0.3444	0.3889	0.38	0.3941	-1.0	-1.0	-1.0	0.1321	0.3889
0.4946	21.0	1953	1.2827	0.1272	0.3247	0.1094	0.0998	0.1661	-1.0	0.1926	0.3259	0.363	0.34	0.3765	-1.0	-1.0	-1.0	0.1272	0.363
0.3004	22.0	2046	1.3022	0.1311	0.2813	0.1268	0.0728	0.1852	-1.0	0.1852	0.3296	0.3778	0.37	0.3824	-1.0	-1.0	-1.0	0.1311	0.3778
0.3004	23.0	2139	1.3196	0.1319	0.2916	0.127	0.0644	0.1938	-1.0	0.1852	0.3222	0.3667	0.34	0.3824	-1.0	-1.0	-1.0	0.1319	0.3667
0.3004	24.0	2232	1.3351	0.137	0.2932	0.1095	0.0663	0.1992	-1.0	0.1852	0.3407	0.3889	0.37	0.4	-1.0	-1.0	-1.0	0.137	0.3889
0.3004	25.0	2325	1.2901	0.1343	0.279	0.1256	0.0743	0.1898	-1.0	0.1963	0.3444	0.3852	0.4	0.3765	-1.0	-1.0	-1.0	0.1343	0.3852
0.3004	26.0	2418	1.3259	0.1361	0.2762	0.1092	0.0648	0.2014	-1.0	0.1889	0.337	0.3889	0.39	0.3882	-1.0	-1.0	-1.0	0.1361	0.3889
0.1909	27.0	2511	1.3338	0.1297	0.2823	0.1118	0.0651	0.1881	-1.0	0.1852	0.3296	0.3778	0.38	0.3765	-1.0	-1.0	-1.0	0.1297	0.3778
0.1909	28.0	2604	1.3253	0.1346	0.2831	0.1119	0.0676	0.1961	-1.0	0.1889	0.337	0.3852	0.39	0.3824	-1.0	-1.0	-1.0	0.1346	0.3852
0.1909	29.0	2697	1.3243	0.1338	0.2829	0.1119	0.0653	0.1961	-1.0	0.1889	0.3333	0.3815	0.38	0.3824	-1.0	-1.0	-1.0	0.1338	0.3815
0.1909	30.0	2790	1.3290	0.1338	0.2829	0.1119	0.0653	0.1961	-1.0	0.1889	0.3333	0.3815	0.38	0.3824	-1.0	-1.0	-1.0	0.1338	0.3815

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1