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--- |
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license: apache-2.0 |
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base_model: facebook/dinov2-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: dino-base-2023_11_20-with_custom_head |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# dino-base-2023_11_20-with_custom_head |
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This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1133 |
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- F1 Micro: 0.8447 |
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- F1 Macro: 0.7988 |
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- Roc Auc: 0.8941 |
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- Accuracy: 0.5681 |
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- Learning Rate: 0.0001 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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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- learning_rate: 0.01 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:------:| |
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| 0.2488 | 1.0 | 536 | 0.2054 | 0.5885 | 0.4304 | 0.7132 | 0.3901 | 0.01 | |
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| 0.219 | 2.0 | 1072 | 0.2322 | 0.6698 | 0.6174 | 0.7719 | 0.4198 | 0.01 | |
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| 0.215 | 3.0 | 1608 | 0.1781 | 0.6953 | 0.5734 | 0.7846 | 0.4073 | 0.01 | |
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| 0.2161 | 4.0 | 2144 | 0.1750 | 0.7345 | 0.6175 | 0.8322 | 0.3901 | 0.01 | |
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| 0.2121 | 5.0 | 2680 | 0.1680 | 0.7332 | 0.5938 | 0.8161 | 0.4344 | 0.01 | |
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| 0.2131 | 6.0 | 3216 | 0.1809 | 0.7109 | 0.5159 | 0.8012 | 0.4259 | 0.01 | |
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| 0.2128 | 7.0 | 3752 | 0.1683 | 0.7151 | 0.5694 | 0.8001 | 0.4284 | 0.01 | |
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| 0.2137 | 8.0 | 4288 | 0.1849 | 0.7333 | 0.5993 | 0.8297 | 0.4098 | 0.01 | |
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| 0.2112 | 9.0 | 4824 | 0.1981 | 0.7056 | 0.6295 | 0.8023 | 0.4130 | 0.01 | |
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| 0.2192 | 10.0 | 5360 | 0.1912 | 0.7417 | 0.6277 | 0.8323 | 0.4212 | 0.01 | |
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| 0.2174 | 11.0 | 5896 | 0.2587 | 0.7234 | 0.6177 | 0.8144 | 0.4173 | 0.01 | |
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| 0.2164 | 12.0 | 6432 | 2.3939 | 0.7708 | 0.6958 | 0.8435 | 0.4691 | 0.001 | |
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| 0.1857 | 13.0 | 6968 | 0.1573 | 0.7965 | 0.7418 | 0.8588 | 0.5023 | 0.001 | |
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| 0.1659 | 14.0 | 7504 | 0.1316 | 0.8104 | 0.7555 | 0.8748 | 0.5148 | 0.001 | |
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| 0.1605 | 15.0 | 8040 | 0.1319 | 0.8114 | 0.7627 | 0.8744 | 0.5138 | 0.001 | |
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| 0.1598 | 16.0 | 8576 | 0.2096 | 0.8137 | 0.7530 | 0.8707 | 0.5305 | 0.001 | |
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| 0.1543 | 17.0 | 9112 | 0.1297 | 0.8221 | 0.7760 | 0.8899 | 0.5148 | 0.001 | |
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| 0.1566 | 18.0 | 9648 | 0.1273 | 0.8266 | 0.7854 | 0.8914 | 0.5259 | 0.001 | |
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| 0.1533 | 19.0 | 10184 | 0.1292 | 0.8189 | 0.7632 | 0.8798 | 0.5216 | 0.001 | |
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| 0.1497 | 20.0 | 10720 | 0.1305 | 0.8273 | 0.7773 | 0.8841 | 0.5198 | 0.001 | |
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| 0.1513 | 21.0 | 11256 | 0.1217 | 0.8290 | 0.7707 | 0.8872 | 0.5295 | 0.001 | |
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| 0.1486 | 22.0 | 11792 | 0.1211 | 0.8268 | 0.7743 | 0.8800 | 0.5420 | 0.001 | |
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| 0.1477 | 23.0 | 12328 | 0.1435 | 0.8210 | 0.7706 | 0.8793 | 0.5263 | 0.001 | |
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| 0.1471 | 24.0 | 12864 | 0.1243 | 0.8277 | 0.7811 | 0.8811 | 0.5370 | 0.001 | |
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| 0.144 | 25.0 | 13400 | 0.1260 | 0.8245 | 0.7752 | 0.8860 | 0.5205 | 0.001 | |
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| 0.1444 | 26.0 | 13936 | 0.1184 | 0.8310 | 0.7857 | 0.8851 | 0.5466 | 0.001 | |
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| 0.1466 | 27.0 | 14472 | 0.1270 | 0.8206 | 0.7654 | 0.8736 | 0.5320 | 0.001 | |
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| 0.1462 | 28.0 | 15008 | 0.1304 | 0.8267 | 0.7756 | 0.8790 | 0.5384 | 0.001 | |
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| 0.1456 | 29.0 | 15544 | 0.1315 | 0.8304 | 0.7897 | 0.8921 | 0.5252 | 0.001 | |
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| 0.144 | 30.0 | 16080 | 0.1236 | 0.8320 | 0.7825 | 0.8846 | 0.5495 | 0.001 | |
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| 0.1429 | 31.0 | 16616 | 0.1284 | 0.8114 | 0.7589 | 0.8700 | 0.5277 | 0.001 | |
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| 0.1467 | 32.0 | 17152 | 0.1222 | 0.8357 | 0.7878 | 0.8916 | 0.5427 | 0.001 | |
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| 0.1388 | 33.0 | 17688 | 0.1284 | 0.8348 | 0.7837 | 0.8857 | 0.5488 | 0.0001 | |
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| 0.1356 | 34.0 | 18224 | 0.1119 | 0.8419 | 0.7958 | 0.8962 | 0.5577 | 0.0001 | |
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| 0.1333 | 35.0 | 18760 | 0.1145 | 0.8408 | 0.7943 | 0.8932 | 0.5627 | 0.0001 | |
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| 0.1292 | 36.0 | 19296 | 0.1136 | 0.8405 | 0.7919 | 0.8918 | 0.5591 | 0.0001 | |
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| 0.1294 | 37.0 | 19832 | 0.1124 | 0.8431 | 0.7990 | 0.8971 | 0.5591 | 0.0001 | |
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| 0.1297 | 38.0 | 20368 | 0.1126 | 0.8407 | 0.7941 | 0.8911 | 0.5638 | 0.0001 | |
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| 0.1259 | 39.0 | 20904 | 0.1121 | 0.8475 | 0.8062 | 0.9007 | 0.5631 | 0.0001 | |
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| 0.1285 | 40.0 | 21440 | 0.1113 | 0.8445 | 0.8013 | 0.8954 | 0.5609 | 0.0001 | |
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| 0.1229 | 41.0 | 21976 | 0.1086 | 0.8465 | 0.8019 | 0.8971 | 0.5663 | 0.0001 | |
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| 0.1234 | 42.0 | 22512 | 0.1093 | 0.8435 | 0.7966 | 0.8941 | 0.5613 | 0.0001 | |
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| 0.1241 | 43.0 | 23048 | 0.1165 | 0.8431 | 0.7990 | 0.8922 | 0.5584 | 0.0001 | |
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| 0.1229 | 44.0 | 23584 | 0.1084 | 0.8446 | 0.8018 | 0.8939 | 0.5663 | 0.0001 | |
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| 0.1205 | 45.0 | 24120 | 0.1073 | 0.8505 | 0.8126 | 0.9030 | 0.5691 | 0.0001 | |
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| 0.1219 | 46.0 | 24656 | 0.1095 | 0.8491 | 0.8142 | 0.9081 | 0.5588 | 0.0001 | |
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| 0.1213 | 47.0 | 25192 | 0.1076 | 0.8486 | 0.8105 | 0.9002 | 0.5688 | 0.0001 | |
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| 0.1205 | 48.0 | 25728 | 0.1131 | 0.8477 | 0.8064 | 0.8999 | 0.5659 | 0.0001 | |
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| 0.1194 | 49.0 | 26264 | 0.1102 | 0.8490 | 0.8107 | 0.9024 | 0.5659 | 0.0001 | |
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| 0.1195 | 50.0 | 26800 | 0.1133 | 0.8447 | 0.7988 | 0.8941 | 0.5681 | 0.0001 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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