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tags:
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- generated_from_trainer
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- accuracy
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model-index:
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- name: DinoVdo-large-2025_01_27_45863-bs32_freeze
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results: []
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---
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should probably proofread and complete it, then remove this comment. -->
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# DinoVdo-large-2025_01_27_45863-bs32_freeze
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This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1236
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- F1 Micro: 0.8136
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- F1 Macro: 0.7060
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- Accuracy: 0.3071
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- Learning Rate: 0.0000
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The following hyperparameters were used during training:
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---
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language:
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- eng
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license: cc0-1.0
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tags:
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- multilabel-image-classification
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- multilabel
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- generated_from_trainer
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base_model: DinoVdo-large-2025_01_27_45863-bs32_freeze
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model-index:
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- name: DinoVdo-large-2025_01_27_45863-bs32_freeze
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results: []
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---
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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:
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- Loss: 0.1236
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- F1 Micro: 0.8136
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- F1 Macro: 0.7060
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- Accuracy: 0.3071
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| Class | F1 per class |
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|----------|-------|
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| Acropore_branched | 0.9015 |
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| Acropore_digitised | 0.6437 |
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| Acropore_sub_massive | 0.3853 |
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| Acropore_tabular | 0.9293 |
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| Algae_assembly | 0.7615 |
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| Algae_drawn_up | 0.4765 |
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| Algae_limestone | 0.7542 |
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| Algae_sodding | 0.8600 |
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| Atra/Leucospilota | 0.8369 |
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| Bleached_coral | 0.6405 |
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| Blurred | 0.6294 |
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| Dead_coral | 0.7340 |
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| Fish | 0.7477 |
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| Homo_sapiens | 0.7788 |
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| Human_object | 0.7629 |
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| Living_coral | 0.6290 |
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| Millepore | 0.8251 |
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| No_acropore_encrusting | 0.6364 |
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| No_acropore_foliaceous | 0.8077 |
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| No_acropore_massive | 0.7208 |
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| No_acropore_solitary | 0.4468 |
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| No_acropore_sub_massive | 0.6970 |
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| Rock | 0.8818 |
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| Rubble | 0.7686 |
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| Sand | 0.9235 |
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| Sea_cucumber | 0.8234 |
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| Sea_urchins | 0.7079 |
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| Sponge | 0.3861 |
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| Syringodium_isoetifolium | 0.9720 |
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| Thalassodendron_ciliatum | 0.9886 |
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| Useless | 0.9745 |
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---
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# Model description
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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.
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The source code for training the model can be found in this [Git repository](https://github.com/SeatizenDOI/DinoVdeau).
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- **Developed by:** [lombardata](https://huggingface.co/lombardata), credits to [César Leblanc](https://huggingface.co/CesarLeblanc) and [Victor Illien](https://huggingface.co/groderg)
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---
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# Intended uses & limitations
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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.
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---
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# Training and evaluation data
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Details on the number of images for each class are given in the following table:
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| Class | train | test | val | Total |
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|:-------------------------|--------:|-------:|------:|--------:|
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| Acropore_branched | 1480 | 469 | 459 | 2408 |
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| Acropore_digitised | 571 | 156 | 161 | 888 |
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| Acropore_sub_massive | 150 | 52 | 41 | 243 |
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| Acropore_tabular | 999 | 292 | 298 | 1589 |
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| Algae_assembly | 2554 | 842 | 842 | 4238 |
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| Algae_drawn_up | 367 | 130 | 123 | 620 |
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| Algae_limestone | 1651 | 562 | 559 | 2772 |
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| Algae_sodding | 3142 | 994 | 981 | 5117 |
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| Atra/Leucospilota | 1084 | 349 | 359 | 1792 |
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| Bleached_coral | 219 | 69 | 72 | 360 |
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| Blurred | 191 | 68 | 61 | 320 |
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| Dead_coral | 1980 | 648 | 636 | 3264 |
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| Fish | 2018 | 661 | 642 | 3321 |
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| Homo_sapiens | 161 | 63 | 58 | 282 |
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| Human_object | 156 | 55 | 59 | 270 |
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| Living_coral | 397 | 151 | 153 | 701 |
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| Millepore | 386 | 127 | 124 | 637 |
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| No_acropore_encrusting | 442 | 141 | 142 | 725 |
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| No_acropore_foliaceous | 204 | 47 | 35 | 286 |
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| No_acropore_massive | 1030 | 341 | 334 | 1705 |
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| No_acropore_solitary | 202 | 55 | 46 | 303 |
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| No_acropore_sub_massive | 1402 | 428 | 426 | 2256 |
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| Rock | 4481 | 1495 | 1481 | 7457 |
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| Rubble | 3092 | 1015 | 1016 | 5123 |
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| Sand | 5839 | 1945 | 1935 | 9719 |
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| Sea_cucumber | 1407 | 437 | 450 | 2294 |
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| Sea_urchins | 328 | 110 | 107 | 545 |
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| Sponge | 267 | 98 | 105 | 470 |
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| Syringodium_isoetifolium | 1213 | 392 | 390 | 1995 |
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| Thalassodendron_ciliatum | 781 | 262 | 260 | 1303 |
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| Useless | 579 | 193 | 193 | 965 |
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---
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# Training procedure
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## Training hyperparameters
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The following hyperparameters were used during training:
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- **Number of Epochs**: 91.0
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- **Learning Rate**: 0.001
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- **Train Batch Size**: 32
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- **Eval Batch Size**: 32
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- **Optimizer**: Adam
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- **LR Scheduler Type**: ReduceLROnPlateau with a patience of 5 epochs and a factor of 0.1
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- **Freeze Encoder**: Yes
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- **Data Augmentation**: Yes
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## Data Augmentation
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Data were augmented using the following transformations :
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Train Transforms
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- **PreProcess**: No additional parameters
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- **Resize**: probability=1.00
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- **RandomHorizontalFlip**: probability=0.25
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- **RandomVerticalFlip**: probability=0.25
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- **ColorJiggle**: probability=0.25
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- **RandomPerspective**: probability=0.25
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- **Normalize**: probability=1.00
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Val Transforms
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- **PreProcess**: No additional parameters
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- **Resize**: probability=1.00
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- **Normalize**: probability=1.00
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## Training results
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Epoch | Validation Loss | Accuracy | F1 Macro | F1 Micro | Learning Rate
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--- | --- | --- | --- | --- | ---
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1 | 0.16775080561637878 | 0.2293 | 0.7433 | 0.5138 | 0.001
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2 | 0.15366077423095703 | 0.2436 | 0.7614 | 0.5771 | 0.001
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3 | 0.14831368625164032 | 0.2415 | 0.7763 | 0.6194 | 0.001
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4 | 0.14640773832798004 | 0.2555 | 0.7808 | 0.6276 | 0.001
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5 | 0.14515382051467896 | 0.2520 | 0.7788 | 0.6421 | 0.001
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6 | 0.14404040575027466 | 0.2579 | 0.7802 | 0.6147 | 0.001
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7 | 0.14518576860427856 | 0.2503 | 0.7787 | 0.6141 | 0.001
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8 | 0.14463570713996887 | 0.2534 | 0.7776 | 0.6193 | 0.001
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9 | 0.14786836504936218 | 0.2454 | 0.7813 | 0.6363 | 0.001
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10 | 0.14251072704792023 | 0.2607 | 0.7866 | 0.6366 | 0.001
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11 | 0.14535894989967346 | 0.2618 | 0.7908 | 0.6566 | 0.001
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12 | 0.14042578637599945 | 0.2600 | 0.7895 | 0.6439 | 0.001
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13 | 0.1413952261209488 | 0.2531 | 0.7883 | 0.6490 | 0.001
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14 | 0.14056158065795898 | 0.2649 | 0.7894 | 0.6348 | 0.001
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15 | 0.13873133063316345 | 0.2632 | 0.7906 | 0.6470 | 0.001
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16 | 0.14008578658103943 | 0.2604 | 0.7858 | 0.6331 | 0.001
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17 | 0.13811993598937988 | 0.2520 | 0.7955 | 0.6651 | 0.001
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18 | 0.13870170712471008 | 0.2702 | 0.7914 | 0.6498 | 0.001
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19 | 0.1373777985572815 | 0.2632 | 0.7940 | 0.6356 | 0.001
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20 | 0.13864819705486298 | 0.2551 | 0.7850 | 0.6393 | 0.001
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21 | 0.13566707074642181 | 0.2646 | 0.7943 | 0.6496 | 0.001
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22 | 0.1371580958366394 | 0.2723 | 0.7972 | 0.6400 | 0.001
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23 | 0.13614478707313538 | 0.2604 | 0.7938 | 0.6595 | 0.001
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24 | 0.1362675279378891 | 0.2649 | 0.7954 | 0.6418 | 0.001
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25 | 0.1358671337366104 | 0.2733 | 0.7963 | 0.6500 | 0.001
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26 | 0.13484793901443481 | 0.2691 | 0.7984 | 0.6555 | 0.001
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27 | 0.13669784367084503 | 0.2688 | 0.7944 | 0.6535 | 0.001
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28 | 0.13569706678390503 | 0.2677 | 0.7923 | 0.6398 | 0.001
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29 | 0.14052562415599823 | 0.2639 | 0.7924 | 0.6637 | 0.001
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30 | 0.13725879788398743 | 0.2723 | 0.7875 | 0.6405 | 0.001
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31 | 0.13544805347919464 | 0.2719 | 0.7986 | 0.6562 | 0.001
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32 | 0.13693773746490479 | 0.2649 | 0.7930 | 0.6463 | 0.001
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33 | 0.13195939362049103 | 0.2747 | 0.8015 | 0.6660 | 0.0001
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+
34 | 0.1299898624420166 | 0.2834 | 0.8043 | 0.6756 | 0.0001
|
| 185 |
+
35 | 0.12946264445781708 | 0.2810 | 0.8066 | 0.6772 | 0.0001
|
| 186 |
+
36 | 0.13086125254631042 | 0.2817 | 0.8046 | 0.6795 | 0.0001
|
| 187 |
+
37 | 0.1278763711452484 | 0.2824 | 0.8054 | 0.6792 | 0.0001
|
| 188 |
+
38 | 0.12904110550880432 | 0.2848 | 0.8078 | 0.6814 | 0.0001
|
| 189 |
+
39 | 0.12716704607009888 | 0.2939 | 0.8116 | 0.6833 | 0.0001
|
| 190 |
+
40 | 0.1293308585882187 | 0.2908 | 0.8116 | 0.6879 | 0.0001
|
| 191 |
+
41 | 0.12695887684822083 | 0.2918 | 0.8089 | 0.6864 | 0.0001
|
| 192 |
+
42 | 0.12624548375606537 | 0.2914 | 0.8109 | 0.6837 | 0.0001
|
| 193 |
+
43 | 0.1261172592639923 | 0.2949 | 0.8123 | 0.6984 | 0.0001
|
| 194 |
+
44 | 0.12830273807048798 | 0.2935 | 0.8106 | 0.6834 | 0.0001
|
| 195 |
+
45 | 0.12624593079090118 | 0.2932 | 0.8113 | 0.7010 | 0.0001
|
| 196 |
+
46 | 0.12462077289819717 | 0.2960 | 0.8147 | 0.6964 | 0.0001
|
| 197 |
+
47 | 0.12529432773590088 | 0.2988 | 0.8126 | 0.6923 | 0.0001
|
| 198 |
+
48 | 0.12631145119667053 | 0.2977 | 0.8133 | 0.6954 | 0.0001
|
| 199 |
+
49 | 0.1252526491880417 | 0.3037 | 0.8158 | 0.6952 | 0.0001
|
| 200 |
+
50 | 0.12632089853286743 | 0.3005 | 0.8136 | 0.7008 | 0.0001
|
| 201 |
+
51 | 0.1246422603726387 | 0.3009 | 0.8158 | 0.7019 | 0.0001
|
| 202 |
+
52 | 0.12534211575984955 | 0.2911 | 0.8092 | 0.6949 | 0.0001
|
| 203 |
+
53 | 0.12436465919017792 | 0.3023 | 0.8154 | 0.7019 | 1e-05
|
| 204 |
+
54 | 0.12488020956516266 | 0.3009 | 0.8154 | 0.7040 | 1e-05
|
| 205 |
+
55 | 0.12366042286157608 | 0.3005 | 0.8144 | 0.6998 | 1e-05
|
| 206 |
+
56 | 0.12352865934371948 | 0.3033 | 0.8168 | 0.7004 | 1e-05
|
| 207 |
+
57 | 0.1239086389541626 | 0.3030 | 0.8157 | 0.7002 | 1e-05
|
| 208 |
+
58 | 0.12343526631593704 | 0.3026 | 0.8157 | 0.6995 | 1e-05
|
| 209 |
+
59 | 0.12345146387815475 | 0.3047 | 0.8150 | 0.7012 | 1e-05
|
| 210 |
+
60 | 0.1239377036690712 | 0.2981 | 0.8128 | 0.6932 | 1e-05
|
| 211 |
+
61 | 0.12398885935544968 | 0.3009 | 0.8174 | 0.7076 | 1e-05
|
| 212 |
+
62 | 0.12334412336349487 | 0.3019 | 0.8152 | 0.7032 | 1e-05
|
| 213 |
+
63 | 0.12325507402420044 | 0.3023 | 0.8158 | 0.7023 | 1e-05
|
| 214 |
+
64 | 0.12346883863210678 | 0.3047 | 0.8152 | 0.6999 | 1e-05
|
| 215 |
+
65 | 0.12324482202529907 | 0.2977 | 0.8145 | 0.7001 | 1e-05
|
| 216 |
+
66 | 0.12292143702507019 | 0.3012 | 0.8145 | 0.7004 | 1e-05
|
| 217 |
+
67 | 0.12375594675540924 | 0.3016 | 0.8159 | 0.6993 | 1e-05
|
| 218 |
+
68 | 0.1228519007563591 | 0.2998 | 0.8176 | 0.7039 | 1e-05
|
| 219 |
+
69 | 0.12302352488040924 | 0.3058 | 0.8157 | 0.7006 | 1e-05
|
| 220 |
+
70 | 0.12284138053655624 | 0.3040 | 0.8170 | 0.7009 | 1e-05
|
| 221 |
+
71 | 0.12295401096343994 | 0.3019 | 0.8158 | 0.7043 | 1e-05
|
| 222 |
+
72 | 0.123215451836586 | 0.3016 | 0.8171 | 0.7025 | 1e-05
|
| 223 |
+
73 | 0.12291014939546585 | 0.3054 | 0.8174 | 0.7049 | 1e-05
|
| 224 |
+
74 | 0.12304174154996872 | 0.3009 | 0.8141 | 0.6942 | 1e-05
|
| 225 |
+
75 | 0.1232200339436531 | 0.3033 | 0.8161 | 0.7001 | 1.0000000000000002e-06
|
| 226 |
+
76 | 0.12267689406871796 | 0.3058 | 0.8171 | 0.7020 | 1.0000000000000002e-06
|
| 227 |
+
77 | 0.12284990400075912 | 0.3079 | 0.8191 | 0.7060 | 1.0000000000000002e-06
|
| 228 |
+
78 | 0.123690165579319 | 0.3019 | 0.8166 | 0.7072 | 1.0000000000000002e-06
|
| 229 |
+
79 | 0.12329532951116562 | 0.3047 | 0.8156 | 0.6992 | 1.0000000000000002e-06
|
| 230 |
+
80 | 0.12325812131166458 | 0.3026 | 0.8172 | 0.6994 | 1.0000000000000002e-06
|
| 231 |
+
81 | 0.12240613251924515 | 0.3054 | 0.8176 | 0.7037 | 1.0000000000000002e-06
|
| 232 |
+
82 | 0.12270382046699524 | 0.3002 | 0.8151 | 0.6972 | 1.0000000000000002e-06
|
| 233 |
+
83 | 0.12315402179956436 | 0.2995 | 0.8146 | 0.6939 | 1.0000000000000002e-06
|
| 234 |
+
84 | 0.1225922629237175 | 0.3026 | 0.8177 | 0.7017 | 1.0000000000000002e-06
|
| 235 |
+
85 | 0.1230376735329628 | 0.3072 | 0.8181 | 0.7059 | 1.0000000000000002e-06
|
| 236 |
+
86 | 0.12335028499364853 | 0.3033 | 0.8168 | 0.7059 | 1.0000000000000002e-06
|
| 237 |
+
87 | 0.12355341017246246 | 0.3005 | 0.8143 | 0.6944 | 1.0000000000000002e-06
|
| 238 |
+
88 | 0.12264065444469452 | 0.3079 | 0.8186 | 0.7029 | 1.0000000000000002e-07
|
| 239 |
+
89 | 0.1229795441031456 | 0.3075 | 0.8179 | 0.7084 | 1.0000000000000002e-07
|
| 240 |
+
90 | 0.12317965924739838 | 0.3037 | 0.8195 | 0.7105 | 1.0000000000000002e-07
|
| 241 |
+
91 | 0.12267619371414185 | 0.3019 | 0.8155 | 0.6972 | 1.0000000000000002e-07
|
| 242 |
+
|
| 243 |
+
|
| 244 |
+
---
|
| 245 |
+
|
| 246 |
+
# Framework Versions
|
| 247 |
+
|
| 248 |
+
- **Transformers**: 4.48.0
|
| 249 |
+
- **Pytorch**: 2.5.1+cu124
|
| 250 |
+
- **Datasets**: 3.0.2
|
| 251 |
+
- **Tokenizers**: 0.21.0
|
| 252 |
+
|