--- language: - eng license: cc0-1.0 tags: - multilabel-image-classification - multilabel - generated_from_trainer base_model: DinoVdo-large-2025_01_27_45863-bs32_freeze model-index: - name: DinoVdo-large-2025_01_27_45863-bs32_freeze results: [] --- DinoVdo is a fine-tuned version of [DinoVdo-large-2025_01_27_45863-bs32_freeze](https://huggingface.co/DinoVdo-large-2025_01_27_45863-bs32_freeze). It achieves the following results on the test set: - Loss: 0.1236 - F1 Micro: 0.8136 - F1 Macro: 0.7060 - Accuracy: 0.3071 | Class | F1 per class | |----------|-------| | Acropore_branched | 0.9015 | | Acropore_digitised | 0.6437 | | Acropore_sub_massive | 0.3853 | | Acropore_tabular | 0.9293 | | Algae_assembly | 0.7615 | | Algae_drawn_up | 0.4765 | | Algae_limestone | 0.7542 | | Algae_sodding | 0.8600 | | Atra/Leucospilota | 0.8369 | | Bleached_coral | 0.6405 | | Blurred | 0.6294 | | Dead_coral | 0.7340 | | Fish | 0.7477 | | Homo_sapiens | 0.7788 | | Human_object | 0.7629 | | Living_coral | 0.6290 | | Millepore | 0.8251 | | No_acropore_encrusting | 0.6364 | | No_acropore_foliaceous | 0.8077 | | No_acropore_massive | 0.7208 | | No_acropore_solitary | 0.4468 | | No_acropore_sub_massive | 0.6970 | | Rock | 0.8818 | | Rubble | 0.7686 | | Sand | 0.9235 | | Sea_cucumber | 0.8234 | | Sea_urchins | 0.7079 | | Sponge | 0.3861 | | Syringodium_isoetifolium | 0.9720 | | Thalassodendron_ciliatum | 0.9886 | | Useless | 0.9745 | --- # Model description DinoVdo is a model built on top of DinoVdo-large-2025_01_27_45863-bs32_freeze model for underwater multilabel image classification.The classification head is a combination of linear, ReLU, batch normalization, and dropout layers. The source code for training the model can be found in this [Git repository](https://github.com/SeatizenDOI/DinoVdeau). - **Developed by:** [lombardata](https://huggingface.co/lombardata), credits to [César Leblanc](https://huggingface.co/CesarLeblanc) and [Victor Illien](https://huggingface.co/groderg) --- # Intended uses & limitations You can use the raw model for classify diverse marine species, encompassing coral morphotypes classes taken from the Global Coral Reef Monitoring Network (GCRMN), habitats classes and seagrass species. --- # Training and evaluation data Details on the number of images for each class are given in the following table: | Class | train | test | val | Total | |:-------------------------|--------:|-------:|------:|--------:| | Acropore_branched | 1480 | 469 | 459 | 2408 | | Acropore_digitised | 571 | 156 | 161 | 888 | | Acropore_sub_massive | 150 | 52 | 41 | 243 | | Acropore_tabular | 999 | 292 | 298 | 1589 | | Algae_assembly | 2554 | 842 | 842 | 4238 | | Algae_drawn_up | 367 | 130 | 123 | 620 | | Algae_limestone | 1651 | 562 | 559 | 2772 | | Algae_sodding | 3142 | 994 | 981 | 5117 | | Atra/Leucospilota | 1084 | 349 | 359 | 1792 | | Bleached_coral | 219 | 69 | 72 | 360 | | Blurred | 191 | 68 | 61 | 320 | | Dead_coral | 1980 | 648 | 636 | 3264 | | Fish | 2018 | 661 | 642 | 3321 | | Homo_sapiens | 161 | 63 | 58 | 282 | | Human_object | 156 | 55 | 59 | 270 | | Living_coral | 397 | 151 | 153 | 701 | | Millepore | 386 | 127 | 124 | 637 | | No_acropore_encrusting | 442 | 141 | 142 | 725 | | No_acropore_foliaceous | 204 | 47 | 35 | 286 | | No_acropore_massive | 1030 | 341 | 334 | 1705 | | No_acropore_solitary | 202 | 55 | 46 | 303 | | No_acropore_sub_massive | 1402 | 428 | 426 | 2256 | | Rock | 4481 | 1495 | 1481 | 7457 | | Rubble | 3092 | 1015 | 1016 | 5123 | | Sand | 5839 | 1945 | 1935 | 9719 | | Sea_cucumber | 1407 | 437 | 450 | 2294 | | Sea_urchins | 328 | 110 | 107 | 545 | | Sponge | 267 | 98 | 105 | 470 | | Syringodium_isoetifolium | 1213 | 392 | 390 | 1995 | | Thalassodendron_ciliatum | 781 | 262 | 260 | 1303 | | Useless | 579 | 193 | 193 | 965 | --- # Training procedure ## Training hyperparameters The following hyperparameters were used during training: - **Number of Epochs**: 91.0 - **Learning Rate**: 0.001 - **Train Batch Size**: 32 - **Eval Batch Size**: 32 - **Optimizer**: Adam - **LR Scheduler Type**: ReduceLROnPlateau with a patience of 5 epochs and a factor of 0.1 - **Freeze Encoder**: Yes - **Data Augmentation**: Yes ## Data Augmentation Data were augmented using the following transformations : Train Transforms - **PreProcess**: No additional parameters - **Resize**: probability=1.00 - **RandomHorizontalFlip**: probability=0.25 - **RandomVerticalFlip**: probability=0.25 - **ColorJiggle**: probability=0.25 - **RandomPerspective**: probability=0.25 - **Normalize**: probability=1.00 Val Transforms - **PreProcess**: No additional parameters - **Resize**: probability=1.00 - **Normalize**: probability=1.00 ## Training results Epoch | Validation Loss | Accuracy | F1 Macro | F1 Micro | Learning Rate --- | --- | --- | --- | --- | --- 1 | 0.16775080561637878 | 0.2293 | 0.7433 | 0.5138 | 0.001 2 | 0.15366077423095703 | 0.2436 | 0.7614 | 0.5771 | 0.001 3 | 0.14831368625164032 | 0.2415 | 0.7763 | 0.6194 | 0.001 4 | 0.14640773832798004 | 0.2555 | 0.7808 | 0.6276 | 0.001 5 | 0.14515382051467896 | 0.2520 | 0.7788 | 0.6421 | 0.001 6 | 0.14404040575027466 | 0.2579 | 0.7802 | 0.6147 | 0.001 7 | 0.14518576860427856 | 0.2503 | 0.7787 | 0.6141 | 0.001 8 | 0.14463570713996887 | 0.2534 | 0.7776 | 0.6193 | 0.001 9 | 0.14786836504936218 | 0.2454 | 0.7813 | 0.6363 | 0.001 10 | 0.14251072704792023 | 0.2607 | 0.7866 | 0.6366 | 0.001 11 | 0.14535894989967346 | 0.2618 | 0.7908 | 0.6566 | 0.001 12 | 0.14042578637599945 | 0.2600 | 0.7895 | 0.6439 | 0.001 13 | 0.1413952261209488 | 0.2531 | 0.7883 | 0.6490 | 0.001 14 | 0.14056158065795898 | 0.2649 | 0.7894 | 0.6348 | 0.001 15 | 0.13873133063316345 | 0.2632 | 0.7906 | 0.6470 | 0.001 16 | 0.14008578658103943 | 0.2604 | 0.7858 | 0.6331 | 0.001 17 | 0.13811993598937988 | 0.2520 | 0.7955 | 0.6651 | 0.001 18 | 0.13870170712471008 | 0.2702 | 0.7914 | 0.6498 | 0.001 19 | 0.1373777985572815 | 0.2632 | 0.7940 | 0.6356 | 0.001 20 | 0.13864819705486298 | 0.2551 | 0.7850 | 0.6393 | 0.001 21 | 0.13566707074642181 | 0.2646 | 0.7943 | 0.6496 | 0.001 22 | 0.1371580958366394 | 0.2723 | 0.7972 | 0.6400 | 0.001 23 | 0.13614478707313538 | 0.2604 | 0.7938 | 0.6595 | 0.001 24 | 0.1362675279378891 | 0.2649 | 0.7954 | 0.6418 | 0.001 25 | 0.1358671337366104 | 0.2733 | 0.7963 | 0.6500 | 0.001 26 | 0.13484793901443481 | 0.2691 | 0.7984 | 0.6555 | 0.001 27 | 0.13669784367084503 | 0.2688 | 0.7944 | 0.6535 | 0.001 28 | 0.13569706678390503 | 0.2677 | 0.7923 | 0.6398 | 0.001 29 | 0.14052562415599823 | 0.2639 | 0.7924 | 0.6637 | 0.001 30 | 0.13725879788398743 | 0.2723 | 0.7875 | 0.6405 | 0.001 31 | 0.13544805347919464 | 0.2719 | 0.7986 | 0.6562 | 0.001 32 | 0.13693773746490479 | 0.2649 | 0.7930 | 0.6463 | 0.001 33 | 0.13195939362049103 | 0.2747 | 0.8015 | 0.6660 | 0.0001 34 | 0.1299898624420166 | 0.2834 | 0.8043 | 0.6756 | 0.0001 35 | 0.12946264445781708 | 0.2810 | 0.8066 | 0.6772 | 0.0001 36 | 0.13086125254631042 | 0.2817 | 0.8046 | 0.6795 | 0.0001 37 | 0.1278763711452484 | 0.2824 | 0.8054 | 0.6792 | 0.0001 38 | 0.12904110550880432 | 0.2848 | 0.8078 | 0.6814 | 0.0001 39 | 0.12716704607009888 | 0.2939 | 0.8116 | 0.6833 | 0.0001 40 | 0.1293308585882187 | 0.2908 | 0.8116 | 0.6879 | 0.0001 41 | 0.12695887684822083 | 0.2918 | 0.8089 | 0.6864 | 0.0001 42 | 0.12624548375606537 | 0.2914 | 0.8109 | 0.6837 | 0.0001 43 | 0.1261172592639923 | 0.2949 | 0.8123 | 0.6984 | 0.0001 44 | 0.12830273807048798 | 0.2935 | 0.8106 | 0.6834 | 0.0001 45 | 0.12624593079090118 | 0.2932 | 0.8113 | 0.7010 | 0.0001 46 | 0.12462077289819717 | 0.2960 | 0.8147 | 0.6964 | 0.0001 47 | 0.12529432773590088 | 0.2988 | 0.8126 | 0.6923 | 0.0001 48 | 0.12631145119667053 | 0.2977 | 0.8133 | 0.6954 | 0.0001 49 | 0.1252526491880417 | 0.3037 | 0.8158 | 0.6952 | 0.0001 50 | 0.12632089853286743 | 0.3005 | 0.8136 | 0.7008 | 0.0001 51 | 0.1246422603726387 | 0.3009 | 0.8158 | 0.7019 | 0.0001 52 | 0.12534211575984955 | 0.2911 | 0.8092 | 0.6949 | 0.0001 53 | 0.12436465919017792 | 0.3023 | 0.8154 | 0.7019 | 1e-05 54 | 0.12488020956516266 | 0.3009 | 0.8154 | 0.7040 | 1e-05 55 | 0.12366042286157608 | 0.3005 | 0.8144 | 0.6998 | 1e-05 56 | 0.12352865934371948 | 0.3033 | 0.8168 | 0.7004 | 1e-05 57 | 0.1239086389541626 | 0.3030 | 0.8157 | 0.7002 | 1e-05 58 | 0.12343526631593704 | 0.3026 | 0.8157 | 0.6995 | 1e-05 59 | 0.12345146387815475 | 0.3047 | 0.8150 | 0.7012 | 1e-05 60 | 0.1239377036690712 | 0.2981 | 0.8128 | 0.6932 | 1e-05 61 | 0.12398885935544968 | 0.3009 | 0.8174 | 0.7076 | 1e-05 62 | 0.12334412336349487 | 0.3019 | 0.8152 | 0.7032 | 1e-05 63 | 0.12325507402420044 | 0.3023 | 0.8158 | 0.7023 | 1e-05 64 | 0.12346883863210678 | 0.3047 | 0.8152 | 0.6999 | 1e-05 65 | 0.12324482202529907 | 0.2977 | 0.8145 | 0.7001 | 1e-05 66 | 0.12292143702507019 | 0.3012 | 0.8145 | 0.7004 | 1e-05 67 | 0.12375594675540924 | 0.3016 | 0.8159 | 0.6993 | 1e-05 68 | 0.1228519007563591 | 0.2998 | 0.8176 | 0.7039 | 1e-05 69 | 0.12302352488040924 | 0.3058 | 0.8157 | 0.7006 | 1e-05 70 | 0.12284138053655624 | 0.3040 | 0.8170 | 0.7009 | 1e-05 71 | 0.12295401096343994 | 0.3019 | 0.8158 | 0.7043 | 1e-05 72 | 0.123215451836586 | 0.3016 | 0.8171 | 0.7025 | 1e-05 73 | 0.12291014939546585 | 0.3054 | 0.8174 | 0.7049 | 1e-05 74 | 0.12304174154996872 | 0.3009 | 0.8141 | 0.6942 | 1e-05 75 | 0.1232200339436531 | 0.3033 | 0.8161 | 0.7001 | 1.0000000000000002e-06 76 | 0.12267689406871796 | 0.3058 | 0.8171 | 0.7020 | 1.0000000000000002e-06 77 | 0.12284990400075912 | 0.3079 | 0.8191 | 0.7060 | 1.0000000000000002e-06 78 | 0.123690165579319 | 0.3019 | 0.8166 | 0.7072 | 1.0000000000000002e-06 79 | 0.12329532951116562 | 0.3047 | 0.8156 | 0.6992 | 1.0000000000000002e-06 80 | 0.12325812131166458 | 0.3026 | 0.8172 | 0.6994 | 1.0000000000000002e-06 81 | 0.12240613251924515 | 0.3054 | 0.8176 | 0.7037 | 1.0000000000000002e-06 82 | 0.12270382046699524 | 0.3002 | 0.8151 | 0.6972 | 1.0000000000000002e-06 83 | 0.12315402179956436 | 0.2995 | 0.8146 | 0.6939 | 1.0000000000000002e-06 84 | 0.1225922629237175 | 0.3026 | 0.8177 | 0.7017 | 1.0000000000000002e-06 85 | 0.1230376735329628 | 0.3072 | 0.8181 | 0.7059 | 1.0000000000000002e-06 86 | 0.12335028499364853 | 0.3033 | 0.8168 | 0.7059 | 1.0000000000000002e-06 87 | 0.12355341017246246 | 0.3005 | 0.8143 | 0.6944 | 1.0000000000000002e-06 88 | 0.12264065444469452 | 0.3079 | 0.8186 | 0.7029 | 1.0000000000000002e-07 89 | 0.1229795441031456 | 0.3075 | 0.8179 | 0.7084 | 1.0000000000000002e-07 90 | 0.12317965924739838 | 0.3037 | 0.8195 | 0.7105 | 1.0000000000000002e-07 91 | 0.12267619371414185 | 0.3019 | 0.8155 | 0.6972 | 1.0000000000000002e-07 --- # Framework Versions - **Transformers**: 4.48.0 - **Pytorch**: 2.5.1+cu124 - **Datasets**: 3.0.2 - **Tokenizers**: 0.21.0