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---
license: apache-2.0
base_model: facebook/dinov2-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: DinoVdeau-large-2024_09_05-batch-size32_epochs150_freeze
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# DinoVdeau-large-2024_09_05-batch-size32_epochs150_freeze
This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1209
- F1 Micro: 0.8228
- F1 Macro: 0.7175
- Roc Auc: 0.8813
- Accuracy: 0.3111
- Learning Rate: 0.0000
## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:------:|
| No log | 1.0 | 273 | 0.1690 | 0.7517 | 0.5430 | 0.8384 | 0.2231 | 0.001 |
| 0.2719 | 2.0 | 546 | 0.1538 | 0.7657 | 0.5721 | 0.8396 | 0.2401 | 0.001 |
| 0.2719 | 3.0 | 819 | 0.1483 | 0.7773 | 0.6138 | 0.8516 | 0.2346 | 0.001 |
| 0.1694 | 4.0 | 1092 | 0.1480 | 0.7723 | 0.6225 | 0.8407 | 0.2495 | 0.001 |
| 0.1694 | 5.0 | 1365 | 0.1458 | 0.7797 | 0.6302 | 0.8470 | 0.2495 | 0.001 |
| 0.1625 | 6.0 | 1638 | 0.1450 | 0.7798 | 0.6093 | 0.8477 | 0.2481 | 0.001 |
| 0.1625 | 7.0 | 1911 | 0.1475 | 0.7767 | 0.6248 | 0.8454 | 0.2526 | 0.001 |
| 0.1592 | 8.0 | 2184 | 0.1457 | 0.7804 | 0.6249 | 0.8521 | 0.2574 | 0.001 |
| 0.1592 | 9.0 | 2457 | 0.1417 | 0.7869 | 0.6526 | 0.8561 | 0.2574 | 0.001 |
| 0.157 | 10.0 | 2730 | 0.1436 | 0.7757 | 0.6290 | 0.8403 | 0.2547 | 0.001 |
| 0.1563 | 11.0 | 3003 | 0.1428 | 0.7887 | 0.6448 | 0.8569 | 0.2640 | 0.001 |
| 0.1563 | 12.0 | 3276 | 0.1439 | 0.7905 | 0.6493 | 0.8638 | 0.2581 | 0.001 |
| 0.1558 | 13.0 | 3549 | 0.1391 | 0.7907 | 0.6562 | 0.8551 | 0.2713 | 0.001 |
| 0.1558 | 14.0 | 3822 | 0.1409 | 0.7838 | 0.6338 | 0.8485 | 0.2644 | 0.001 |
| 0.1543 | 15.0 | 4095 | 0.1396 | 0.7907 | 0.6463 | 0.8603 | 0.2578 | 0.001 |
| 0.1543 | 16.0 | 4368 | 0.1390 | 0.7913 | 0.6594 | 0.8564 | 0.2654 | 0.001 |
| 0.1535 | 17.0 | 4641 | 0.1418 | 0.7940 | 0.6586 | 0.8665 | 0.2564 | 0.001 |
| 0.1535 | 18.0 | 4914 | 0.1416 | 0.7957 | 0.6560 | 0.8646 | 0.2658 | 0.001 |
| 0.1549 | 19.0 | 5187 | 0.1403 | 0.7886 | 0.6524 | 0.8536 | 0.2630 | 0.001 |
| 0.1549 | 20.0 | 5460 | 0.1476 | 0.7911 | 0.6558 | 0.8568 | 0.2613 | 0.001 |
| 0.154 | 21.0 | 5733 | 0.1429 | 0.7880 | 0.6397 | 0.8568 | 0.2658 | 0.001 |
| 0.1529 | 22.0 | 6006 | 0.1414 | 0.7937 | 0.6508 | 0.8654 | 0.2613 | 0.001 |
| 0.1529 | 23.0 | 6279 | 0.1415 | 0.7976 | 0.6618 | 0.8613 | 0.2685 | 0.0001 |
| 0.1449 | 24.0 | 6552 | 0.1323 | 0.8045 | 0.6751 | 0.8665 | 0.2789 | 0.0001 |
| 0.1449 | 25.0 | 6825 | 0.1310 | 0.8044 | 0.6724 | 0.8688 | 0.2793 | 0.0001 |
| 0.1416 | 26.0 | 7098 | 0.1327 | 0.8036 | 0.6689 | 0.8646 | 0.2821 | 0.0001 |
| 0.1416 | 27.0 | 7371 | 0.1317 | 0.8069 | 0.6797 | 0.8715 | 0.2817 | 0.0001 |
| 0.1391 | 28.0 | 7644 | 0.1288 | 0.8072 | 0.6818 | 0.8698 | 0.2775 | 0.0001 |
| 0.1391 | 29.0 | 7917 | 0.1294 | 0.8038 | 0.6808 | 0.8629 | 0.2845 | 0.0001 |
| 0.138 | 30.0 | 8190 | 0.1294 | 0.8077 | 0.6826 | 0.8702 | 0.2859 | 0.0001 |
| 0.138 | 31.0 | 8463 | 0.1274 | 0.8074 | 0.6779 | 0.8666 | 0.2879 | 0.0001 |
| 0.1364 | 32.0 | 8736 | 0.1278 | 0.8104 | 0.6869 | 0.8728 | 0.2883 | 0.0001 |
| 0.1359 | 33.0 | 9009 | 0.1277 | 0.8077 | 0.6811 | 0.8692 | 0.2869 | 0.0001 |
| 0.1359 | 34.0 | 9282 | 0.1266 | 0.8109 | 0.6874 | 0.8714 | 0.2883 | 0.0001 |
| 0.1341 | 35.0 | 9555 | 0.1262 | 0.8104 | 0.6885 | 0.8716 | 0.2904 | 0.0001 |
| 0.1341 | 36.0 | 9828 | 0.1269 | 0.8070 | 0.6876 | 0.8657 | 0.2827 | 0.0001 |
| 0.1339 | 37.0 | 10101 | 0.1266 | 0.8082 | 0.6834 | 0.8678 | 0.2866 | 0.0001 |
| 0.1339 | 38.0 | 10374 | 0.1255 | 0.8106 | 0.6936 | 0.8707 | 0.2956 | 0.0001 |
| 0.1307 | 39.0 | 10647 | 0.1249 | 0.8142 | 0.6986 | 0.8768 | 0.2928 | 0.0001 |
| 0.1307 | 40.0 | 10920 | 0.1258 | 0.8138 | 0.6990 | 0.8773 | 0.2935 | 0.0001 |
| 0.1317 | 41.0 | 11193 | 0.1253 | 0.8101 | 0.6924 | 0.8688 | 0.2924 | 0.0001 |
| 0.1317 | 42.0 | 11466 | 0.1244 | 0.8138 | 0.6970 | 0.8738 | 0.3004 | 0.0001 |
| 0.1308 | 43.0 | 11739 | 0.1245 | 0.8131 | 0.6956 | 0.8734 | 0.2949 | 0.0001 |
| 0.1307 | 44.0 | 12012 | 0.1250 | 0.8130 | 0.6915 | 0.8743 | 0.2966 | 0.0001 |
| 0.1307 | 45.0 | 12285 | 0.1240 | 0.8137 | 0.7051 | 0.8740 | 0.2963 | 0.0001 |
| 0.1295 | 46.0 | 12558 | 0.1241 | 0.8131 | 0.6988 | 0.8733 | 0.2976 | 0.0001 |
| 0.1295 | 47.0 | 12831 | 0.1243 | 0.8119 | 0.6958 | 0.8716 | 0.2956 | 0.0001 |
| 0.1293 | 48.0 | 13104 | 0.1239 | 0.8135 | 0.6990 | 0.8744 | 0.2956 | 0.0001 |
| 0.1293 | 49.0 | 13377 | 0.1243 | 0.8153 | 0.7007 | 0.8775 | 0.2997 | 0.0001 |
| 0.1274 | 50.0 | 13650 | 0.1241 | 0.8152 | 0.7000 | 0.8769 | 0.2980 | 0.0001 |
| 0.1274 | 51.0 | 13923 | 0.1248 | 0.8153 | 0.7056 | 0.8803 | 0.3011 | 0.0001 |
| 0.1271 | 52.0 | 14196 | 0.1243 | 0.8157 | 0.7036 | 0.8751 | 0.3049 | 0.0001 |
| 0.1271 | 53.0 | 14469 | 0.1241 | 0.8153 | 0.7032 | 0.8778 | 0.3021 | 0.0001 |
| 0.1275 | 54.0 | 14742 | 0.1234 | 0.8152 | 0.7068 | 0.8753 | 0.3021 | 0.0001 |
| 0.1256 | 55.0 | 15015 | 0.1231 | 0.8166 | 0.7076 | 0.8776 | 0.3018 | 0.0001 |
| 0.1256 | 56.0 | 15288 | 0.1228 | 0.8190 | 0.7088 | 0.8822 | 0.3067 | 0.0001 |
| 0.1258 | 57.0 | 15561 | 0.1226 | 0.8160 | 0.7080 | 0.8767 | 0.3070 | 0.0001 |
| 0.1258 | 58.0 | 15834 | 0.1233 | 0.8170 | 0.7073 | 0.8773 | 0.3021 | 0.0001 |
| 0.1258 | 59.0 | 16107 | 0.1227 | 0.8172 | 0.7135 | 0.8781 | 0.3021 | 0.0001 |
| 0.1258 | 60.0 | 16380 | 0.1233 | 0.8143 | 0.7040 | 0.8729 | 0.3021 | 0.0001 |
| 0.1252 | 61.0 | 16653 | 0.1234 | 0.8168 | 0.7121 | 0.8784 | 0.3042 | 0.0001 |
| 0.1252 | 62.0 | 16926 | 0.1223 | 0.8169 | 0.7125 | 0.8764 | 0.3049 | 0.0001 |
| 0.1238 | 63.0 | 17199 | 0.1231 | 0.8151 | 0.7090 | 0.8752 | 0.3035 | 0.0001 |
| 0.1238 | 64.0 | 17472 | 0.1228 | 0.8183 | 0.7114 | 0.8785 | 0.3067 | 0.0001 |
| 0.1247 | 65.0 | 17745 | 0.1231 | 0.8185 | 0.7156 | 0.8802 | 0.3035 | 0.0001 |
| 0.123 | 66.0 | 18018 | 0.1225 | 0.8193 | 0.7084 | 0.8809 | 0.3021 | 0.0001 |
| 0.123 | 67.0 | 18291 | 0.1222 | 0.8186 | 0.7136 | 0.8814 | 0.3032 | 0.0001 |
| 0.1224 | 68.0 | 18564 | 0.1220 | 0.8201 | 0.7169 | 0.8818 | 0.3091 | 0.0001 |
| 0.1224 | 69.0 | 18837 | 0.1228 | 0.8171 | 0.7165 | 0.8768 | 0.3018 | 0.0001 |
| 0.1228 | 70.0 | 19110 | 0.1227 | 0.8177 | 0.7131 | 0.8765 | 0.3042 | 0.0001 |
| 0.1228 | 71.0 | 19383 | 0.1232 | 0.8155 | 0.7123 | 0.8733 | 0.2980 | 0.0001 |
| 0.1224 | 72.0 | 19656 | 0.1222 | 0.8177 | 0.7181 | 0.8780 | 0.3056 | 0.0001 |
| 0.1224 | 73.0 | 19929 | 0.1221 | 0.8162 | 0.7047 | 0.8760 | 0.3077 | 0.0001 |
| 0.122 | 74.0 | 20202 | 0.1230 | 0.8148 | 0.7070 | 0.8732 | 0.2973 | 0.0001 |
| 0.122 | 75.0 | 20475 | 0.1214 | 0.8176 | 0.7124 | 0.8768 | 0.3049 | 1e-05 |
| 0.1201 | 76.0 | 20748 | 0.1209 | 0.8213 | 0.7265 | 0.8828 | 0.3067 | 1e-05 |
| 0.1192 | 77.0 | 21021 | 0.1216 | 0.8221 | 0.7249 | 0.8860 | 0.3073 | 1e-05 |
| 0.1192 | 78.0 | 21294 | 0.1211 | 0.8210 | 0.7233 | 0.8828 | 0.3056 | 1e-05 |
| 0.1178 | 79.0 | 21567 | 0.1211 | 0.8181 | 0.7158 | 0.8769 | 0.3056 | 1e-05 |
| 0.1178 | 80.0 | 21840 | 0.1210 | 0.8200 | 0.7197 | 0.8824 | 0.3091 | 1e-05 |
| 0.1178 | 81.0 | 22113 | 0.1205 | 0.8190 | 0.7194 | 0.8784 | 0.3105 | 1e-05 |
| 0.1178 | 82.0 | 22386 | 0.1205 | 0.8187 | 0.7213 | 0.8782 | 0.3070 | 1e-05 |
| 0.1162 | 83.0 | 22659 | 0.1215 | 0.8171 | 0.7136 | 0.8754 | 0.3049 | 1e-05 |
| 0.1162 | 84.0 | 22932 | 0.1209 | 0.8212 | 0.7226 | 0.8817 | 0.3115 | 1e-05 |
| 0.1174 | 85.0 | 23205 | 0.1206 | 0.8213 | 0.7219 | 0.8823 | 0.3094 | 1e-05 |
| 0.1174 | 86.0 | 23478 | 0.1210 | 0.8207 | 0.7256 | 0.8811 | 0.3084 | 1e-05 |
| 0.1167 | 87.0 | 23751 | 0.1210 | 0.8192 | 0.7163 | 0.8800 | 0.3073 | 1e-05 |
| 0.116 | 88.0 | 24024 | 0.1208 | 0.8219 | 0.7180 | 0.8831 | 0.3094 | 1e-05 |
| 0.116 | 89.0 | 24297 | 0.1213 | 0.8236 | 0.7293 | 0.8872 | 0.3125 | 0.0000 |
| 0.1161 | 90.0 | 24570 | 0.1211 | 0.8228 | 0.7250 | 0.8869 | 0.3108 | 0.0000 |
| 0.1161 | 91.0 | 24843 | 0.1206 | 0.8191 | 0.7187 | 0.8779 | 0.3105 | 0.0000 |
| 0.1162 | 92.0 | 25116 | 0.1208 | 0.8196 | 0.7150 | 0.8793 | 0.3105 | 0.0000 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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