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slnkvdns/finetune-instance-segmentation-alpha-dent-mask2former-base

sourceHugging Faceotherupdated 4mo agoView on Hugging Face

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finetune-instance-segmentation-alpha-dent-mask2former-base

This model is a fine-tuned version of facebook/mask2former-swin-small-coco-instance on the slnkvdns/AlphaDent dataset. It achieves the following results on the evaluation set:

—Loss: 24.9112
—Map: 0.2883
—Map 50: 0.4168
—Map 75: 0.2833
—Map Small: 0.1263
—Map Medium: 0.3228
—Map Large: 0.7868
—Mar 1: 0.1931
—Mar 10: 0.3716
—Mar 100: 0.3891
—Mar Small: 0.2192
—Mar Medium: 0.4104
—Mar Large: 0.89
—Map Background: 0.9602
—Mar 100 Background: 0.9699
—Map Abrasion: 0.7008
—Mar 100 Abrasion: 0.8541
—Map Filling: 0.2203
—Mar 100 Filling: 0.3536
—Map Crown: 0.7002
—Mar 100 Crown: 0.8053
—Map Caries class 1: 0.1182
—Mar 100 Caries class 1: 0.2741
—Map Caries class 2: 0.0324
—Mar 100 Caries class 2: 0.1861
—Map Caries class 3: 0.0067
—Mar 100 Caries class 3: 0.0788
—Map Caries class 4: 0.0224
—Mar 100 Caries class 4: 0.1
—Map Caries class 5: 0.1209
—Mar 100 Caries class 5: 0.2487
—Map Caries class 6: 0.0008
—Mar 100 Caries class 6: 0.02

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: 4e-05
—trainbatchsize: 4
—evalbatchsize: 8
—seed: 42
—gradientaccumulationsteps: 2
—totaltrainbatch_size: 8
—optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
—lrschedulertype: constant
—num_epochs: 10.0
—mixedprecisiontraining: Native AMP

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 Abrasion	Mar 100 Abrasion	Map Filling	Mar 100 Filling	Map Crown	Mar 100 Crown	Map Caries class 1	Mar 100 Caries class 1	Map Caries class 2	Mar 100 Caries class 2	Map Caries class 3	Mar 100 Caries class 3	Map Caries class 4	Mar 100 Caries class 4	Map Caries class 5	Mar 100 Caries class 5	Map Caries class 6	Mar 100 Caries class 6
45.8256	1.0	155	36.5384	0.1558	0.1945	0.17	0.0821	0.0991	0.3994	0.1104	0.202	0.2208	0.1227	0.1912	0.6044	0.8982	0.9133	0.5921	0.8283	0.0279	0.2145	0.0	0.0	0.0051	0.0414	0.0005	0.0333	0.0009	0.0121	0.0	0.0	0.0327	0.1654	0.0	0.0
33.1372	2.0	310	31.3143	0.1952	0.265	0.2015	0.0912	0.1876	0.7196	0.1495	0.3013	0.3234	0.1635	0.3368	0.9014	0.9403	0.9542	0.6287	0.8278	0.1051	0.276	0.1867	0.6368	0.03	0.2328	0.0058	0.0903	0.0012	0.0212	0.0	0.0	0.0546	0.1949	0.0	0.0
29.0343	3.0	465	29.2439	0.2207	0.3169	0.2227	0.0998	0.2434	0.8249	0.1498	0.3302	0.3485	0.1768	0.4005	0.9371	0.9496	0.9614	0.6151	0.8253	0.132	0.2961	0.3515	0.7526	0.0745	0.2362	0.0107	0.1319	0.0008	0.0455	0.0	0.0	0.0732	0.2359	0.0	0.0
26.3806	4.0	620	26.8526	0.2641	0.3736	0.2652	0.1086	0.2931	0.7625	0.1811	0.3354	0.3542	0.1811	0.409	0.9392	0.9569	0.9675	0.6843	0.8511	0.1786	0.3089	0.6277	0.7474	0.0791	0.2552	0.0141	0.1306	0.0018	0.0485	0.0	0.0	0.0987	0.2333	0.0	0.0
24.5939	5.0	775	26.1020	0.2691	0.3766	0.269	0.1092	0.3087	0.7244	0.1783	0.3438	0.3618	0.1841	0.4174	0.9404	0.9605	0.9711	0.6849	0.8469	0.1718	0.3145	0.6582	0.7947	0.0893	0.2448	0.0236	0.1667	0.0013	0.0545	0.0	0.0	0.1019	0.2244	0.0	0.0
22.9142	6.0	930	24.8907	0.2786	0.3964	0.279	0.1147	0.3172	0.8896	0.1774	0.3462	0.3614	0.1851	0.4225	0.9416	0.9669	0.9747	0.7054	0.8599	0.1808	0.3106	0.671	0.7474	0.1146	0.2569	0.0162	0.1611	0.0038	0.0485	0.0	0.0	0.1271	0.2551	0.0	0.0
21.8794	7.0	1085	24.7008	0.2827	0.4036	0.2816	0.1175	0.316	0.7695	0.1805	0.351	0.3688	0.1947	0.4051	0.9229	0.9584	0.9687	0.6885	0.8531	0.1799	0.3123	0.7385	0.8053	0.1052	0.231	0.0247	0.1875	0.0141	0.0788	0.0	0.0	0.1174	0.2513	0.0	0.0
20.8095	8.0	1240	24.1177	0.2921	0.4443	0.295	0.1271	0.3495	0.8291	0.1924	0.3698	0.3832	0.2103	0.4345	0.9408	0.9619	0.9723	0.6979	0.8519	0.214	0.3559	0.7118	0.7947	0.1017	0.2483	0.034	0.1708	0.0059	0.0758	0.0515	0.05	0.1278	0.2526	0.0142	0.06
19.6702	9.0	1395	24.5206	0.2803	0.4177	0.277	0.123	0.3215	0.7562	0.181	0.3631	0.3817	0.2104	0.4352	0.9237	0.9632	0.9711	0.7038	0.8569	0.2199	0.3419	0.6239	0.7579	0.0982	0.2724	0.0263	0.1667	0.005	0.0818	0.0	0.0	0.1349	0.2679	0.0276	0.1
18.6977	10.0	1550	24.9112	0.2883	0.4168	0.2833	0.1263	0.3228	0.7868	0.1931	0.3716	0.3891	0.2192	0.4104	0.89	0.9602	0.9699	0.7008	0.8541	0.2203	0.3536	0.7002	0.8053	0.1182	0.2741	0.0324	0.1861	0.0067	0.0788	0.0224	0.1	0.1209	0.2487	0.0008	0.02

Framework versions

—Transformers 5.0.0
—Pytorch 2.10.0+cu128
—Datasets 4.8.3
—Tokenizers 0.22.2