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
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • 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: constant
  • num_epochs: 10.0
  • mixed_precision_training: 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
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