argos-dentsight-stage2-conditions-v4

This model is a fine-tuned version of Mobe1/argos-dentsight-stage2-conditions-v3 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.8800
• Map: 0.4331
• Map 50: 0.5866
• Map 75: 0.4683
• Map Small: 0.046
• Map Medium: 0.4224
• Map Large: 0.4605
• Mar 1: 0.2348
• Mar 10: 0.574
• Mar 100: 0.5947
• Mar Small: 0.1361
• Mar Medium: 0.5974
• Mar Large: 0.6607
• Map Rc-treated: 0.7236
• Mar 100 Rc-treated: 0.8204
• Map Bridge: 0.7044
• Mar 100 Bridge: 0.8463
• Map Calculus: 0.0228
• Mar 100 Calculus: 0.1769
• Map Caries: 0.0706
• Mar 100 Caries: 0.2785
• Map Crown: 0.7386
• Mar 100 Crown: 0.8759
• Map Impacted: 0.7186
• Mar 100 Impacted: 0.8926
• Map Implant: 0.7459
• Mar 100 Implant: 0.8329
• Map Missing: 0.2501
• Mar 100 Missing: 0.3843
• Map Other-finding: 0.0841
• Mar 100 Other-finding: 0.3846
• Map Periapical-radiolucency: 0.0745
• Mar 100 Periapical-radiolucency: 0.2142
• Map Restoration: 0.3504
• Mar 100 Restoration: 0.4617
• Map Root-stump: 0.4743
• Mar 100 Root-stump: 0.6753
• Map Tooth-bud: 0.6728
• Mar 100 Tooth-bud: 0.8875

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: 4
• eval_batch_size: 2
• 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_ratio: 0.05
• num_epochs: 18.0

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 Rc-treated	Mar 100 Rc-treated	Map Bridge	Mar 100 Bridge	Map Calculus	Mar 100 Calculus	Map Caries	Mar 100 Caries	Map Crown	Mar 100 Crown	Map Impacted	Mar 100 Impacted	Map Implant	Mar 100 Implant	Map Missing	Mar 100 Missing	Map Other-finding	Mar 100 Other-finding	Map Periapical-radiolucency	Mar 100 Periapical-radiolucency	Map Restoration	Mar 100 Restoration	Map Root-stump	Mar 100 Root-stump	Map Tooth-bud	Mar 100 Tooth-bud
21.154	1.0	557	2.7684	0.4177	0.5542	0.4531	0.0387	0.3998	0.454	0.2259	0.5577	0.5785	0.097	0.6031	0.6146	0.7236	0.8118	0.7264	0.8894	0.0331	0.166	0.03	0.2287	0.7102	0.8799	0.6568	0.8943	0.7399	0.8197	0.2242	0.3501	0.1087	0.3288	0.0565	0.229	0.331	0.4173	0.4013	0.6131	0.6879	0.8917
21.8071	2.0	1114	2.6982	0.4274	0.5723	0.4638	0.0392	0.4135	0.4624	0.2334	0.5732	0.5912	0.1008	0.6142	0.6285	0.7158	0.813	0.6905	0.887	0.0253	0.1603	0.0293	0.2361	0.7341	0.8617	0.6878	0.8993	0.768	0.8395	0.2225	0.3473	0.1087	0.4365	0.0594	0.1882	0.3521	0.483	0.4492	0.6335	0.7134	0.9
21.6791	3.0	1671	2.7436	0.4321	0.5807	0.4652	0.0457	0.4049	0.461	0.2466	0.5825	0.6073	0.1138	0.6352	0.6407	0.7239	0.8143	0.6748	0.8992	0.0265	0.1612	0.0457	0.2832	0.7246	0.8769	0.6852	0.8998	0.7498	0.8395	0.2248	0.3509	0.1418	0.5115	0.0857	0.2163	0.3564	0.4938	0.465	0.6781	0.7128	0.8708
21.4852	4.0	2228	2.6003	0.449	0.6012	0.4847	0.0459	0.4388	0.4855	0.2418	0.5876	0.6127	0.1248	0.6289	0.6651	0.7417	0.8309	0.7348	0.9154	0.0225	0.1466	0.0714	0.3212	0.7375	0.8811	0.7294	0.9097	0.7633	0.8329	0.2411	0.3699	0.1552	0.4481	0.0733	0.216	0.3739	0.5158	0.4658	0.6904	0.7272	0.8875
21.4971	5.0	2785	2.7692	0.4338	0.5751	0.4733	0.0433	0.4226	0.4559	0.2349	0.5798	0.6063	0.1181	0.6277	0.7094	0.7264	0.8309	0.701	0.8967	0.0196	0.1508	0.0469	0.2765	0.7359	0.8838	0.7287	0.8945	0.7429	0.8197	0.216	0.3436	0.1251	0.4654	0.0763	0.2505	0.3709	0.5249	0.4505	0.6486	0.6988	0.8958
21.0136	6.0	3342	2.6982	0.4341	0.5821	0.4723	0.0455	0.4164	0.4643	0.2442	0.5807	0.6073	0.115	0.6136	0.678	0.7352	0.8261	0.678	0.8886	0.0358	0.1771	0.0519	0.2844	0.7163	0.8714	0.7173	0.8989	0.7533	0.8395	0.2417	0.3702	0.1291	0.4827	0.08	0.2154	0.3385	0.4768	0.4653	0.6765	0.701	0.8875
20.883	7.0	3899	2.7700	0.4336	0.5767	0.4706	0.0445	0.4193	0.45	0.2365	0.5811	0.6056	0.1398	0.6197	0.6717	0.7299	0.834	0.6733	0.8813	0.023	0.1751	0.0394	0.2756	0.7309	0.8739	0.7025	0.8943	0.7464	0.8289	0.2236	0.3708	0.1096	0.4692	0.0638	0.2094	0.3615	0.4906	0.4574	0.6777	0.7749	0.8917
20.4566	8.0	4456	2.8283	0.4354	0.5833	0.4692	0.0398	0.4154	0.4658	0.2353	0.5744	0.5967	0.1024	0.6141	0.6327	0.7291	0.8235	0.691	0.8699	0.0251	0.1623	0.0347	0.247	0.7185	0.8649	0.7257	0.8979	0.7619	0.8382	0.2418	0.3842	0.0964	0.4365	0.0726	0.2257	0.341	0.4393	0.4706	0.6761	0.7518	0.8917
20.0491	9.0	5013	2.8166	0.4365	0.5855	0.4738	0.0491	0.4256	0.4698	0.2382	0.583	0.6071	0.1226	0.6071	0.6753	0.7315	0.8289	0.6859	0.8561	0.0271	0.1714	0.0747	0.3047	0.7369	0.8794	0.7306	0.9062	0.753	0.8329	0.2501	0.3817	0.0849	0.4442	0.0772	0.2184	0.3604	0.4857	0.4852	0.6956	0.677	0.8875
19.7247	10.0	5570	2.8688	0.4333	0.5784	0.4694	0.0451	0.432	0.4578	0.2357	0.5765	0.5981	0.1144	0.6023	0.6449	0.7236	0.822	0.6917	0.848	0.0146	0.1497	0.0573	0.2913	0.7216	0.8766	0.7325	0.9025	0.756	0.8303	0.2429	0.3777	0.1088	0.4096	0.0731	0.2221	0.3527	0.4721	0.4591	0.6781	0.6988	0.8958
19.3504	11.0	6127	2.8230	0.4418	0.5959	0.4803	0.0476	0.4291	0.4667	0.2413	0.5849	0.6104	0.1473	0.6209	0.6875	0.7253	0.8151	0.7074	0.8707	0.0172	0.1798	0.066	0.3128	0.7386	0.8764	0.7331	0.9037	0.7522	0.8408	0.252	0.387	0.1285	0.4731	0.0794	0.2254	0.3523	0.4696	0.4698	0.6845	0.7221	0.8958
19.1338	12.0	6684	2.8955	0.4384	0.5888	0.4768	0.0465	0.4271	0.4678	0.2339	0.5811	0.6016	0.1271	0.6098	0.6793	0.7188	0.812	0.7056	0.848	0.0207	0.1712	0.0634	0.2749	0.7324	0.8808	0.7395	0.9	0.7578	0.8368	0.2476	0.3772	0.0967	0.475	0.0729	0.2082	0.3577	0.4719	0.4698	0.6733	0.7157	0.8917
18.7777	13.0	7241	2.9031	0.4308	0.581	0.466	0.0478	0.4204	0.4597	0.2311	0.5799	0.6013	0.1371	0.6176	0.6585	0.724	0.8199	0.6955	0.8683	0.02	0.1715	0.058	0.2702	0.7248	0.8761	0.7206	0.8947	0.7475	0.8329	0.2475	0.3847	0.0892	0.4615	0.0788	0.2215	0.3623	0.4753	0.4737	0.6741	0.6593	0.8667
18.5211	14.0	7798	2.8804	0.4364	0.5872	0.4725	0.0461	0.4243	0.467	0.237	0.5789	0.6003	0.1126	0.6037	0.6639	0.725	0.8199	0.6988	0.8512	0.0211	0.1666	0.0698	0.2908	0.7269	0.8759	0.7348	0.9037	0.7539	0.8408	0.2458	0.3809	0.0865	0.4135	0.0754	0.2254	0.3541	0.4654	0.462	0.6745	0.7185	0.8958
18.3289	15.0	8355	2.8782	0.4337	0.5859	0.4692	0.0463	0.4213	0.4648	0.2335	0.5728	0.5927	0.1175	0.5876	0.6244	0.7247	0.8184	0.7037	0.8415	0.0219	0.1746	0.0698	0.2789	0.7351	0.8764	0.7221	0.8899	0.7505	0.8355	0.2516	0.3862	0.0935	0.3923	0.0751	0.2094	0.3487	0.4563	0.4685	0.6753	0.6732	0.8708
18.1294	16.0	8912	2.8917	0.4333	0.5854	0.4701	0.0464	0.4225	0.4604	0.2338	0.5743	0.5966	0.1366	0.608	0.661	0.7237	0.821	0.703	0.8585	0.021	0.1768	0.0648	0.2755	0.7344	0.8759	0.7202	0.8917	0.7528	0.8368	0.2502	0.3846	0.0817	0.3865	0.0747	0.2148	0.3534	0.4677	0.4755	0.6781	0.6775	0.8875
17.8753	17.0	9469	2.8867	0.4323	0.5847	0.468	0.046	0.4202	0.4627	0.2334	0.5725	0.5939	0.1361	0.5965	0.6608	0.7239	0.8194	0.7068	0.8463	0.022	0.1762	0.0689	0.2783	0.7383	0.8751	0.7192	0.8924	0.7468	0.8342	0.2504	0.384	0.0808	0.3769	0.0753	0.2145	0.3502	0.4617	0.475	0.6745	0.6624	0.8875
17.8355	18.0	10026	2.8800	0.4331	0.5866	0.4683	0.046	0.4224	0.4605	0.2348	0.574	0.5947	0.1361	0.5974	0.6607	0.7236	0.8204	0.7044	0.8463	0.0228	0.1769	0.0706	0.2785	0.7386	0.8759	0.7186	0.8926	0.7459	0.8329	0.2501	0.3843	0.0841	0.3846	0.0745	0.2142	0.3504	0.4617	0.4743	0.6753	0.6728	0.8875

Framework versions

• Transformers 4.57.6
• Pytorch 2.11.0+cu130
• Datasets 4.8.5
• Tokenizers 0.22.2