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# dino-large-2023_12_08-with_custom_head-imgsize1036

This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the multilabel_complete_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1017
- F1 Micro: 0.8547
- F1 Macro: 0.8214
- Roc Auc: 0.9081
- Accuracy: 0.5649
- Learning Rate: 0.0001

## 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: 0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:------:|
| 0.2502        | 1.0   | 536   | 0.1990          | 0.6427   | 0.5121   | 0.7510  | 0.4030   | 0.01   |
| 0.2164        | 2.0   | 1072  | 1.1451          | 0.6769   | 0.6296   | 0.7895  | 0.4048   | 0.01   |
| 0.2149        | 3.0   | 1608  | 0.2339          | 0.6516   | 0.5251   | 0.7524  | 0.3994   | 0.01   |
| 0.2159        | 4.0   | 2144  | 0.1699          | 0.7376   | 0.6028   | 0.8297  | 0.4116   | 0.01   |
| 0.2171        | 5.0   | 2680  | 0.1650          | 0.7364   | 0.6304   | 0.8166  | 0.4394   | 0.01   |
| 0.2166        | 6.0   | 3216  | 0.1748          | 0.6853   | 0.5123   | 0.7773  | 0.3923   | 0.01   |
| 0.2081        | 7.0   | 3752  | 0.1636          | 0.7455   | 0.6129   | 0.8291  | 0.4348   | 0.01   |
| 0.2111        | 8.0   | 4288  | 0.1651          | 0.7543   | 0.6445   | 0.8476  | 0.4277   | 0.01   |
| 0.209         | 9.0   | 4824  | 0.1750          | 0.7062   | 0.6522   | 0.7966  | 0.4359   | 0.01   |
| 0.2107        | 10.0  | 5360  | 0.1751          | 0.7244   | 0.5924   | 0.8146  | 0.3830   | 0.01   |
| 0.2162        | 11.0  | 5896  | 0.2229          | 0.7506   | 0.6780   | 0.8475  | 0.4252   | 0.01   |
| 0.2153        | 12.0  | 6432  | 0.1740          | 0.7501   | 0.6543   | 0.8550  | 0.4105   | 0.01   |
| 0.2197        | 13.0  | 6968  | 0.1745          | 0.7487   | 0.6605   | 0.8572  | 0.4187   | 0.01   |
| 0.18          | 14.0  | 7504  | 0.1348          | 0.8036   | 0.7455   | 0.8731  | 0.5059   | 0.001  |
| 0.164         | 15.0  | 8040  | 0.1308          | 0.8160   | 0.7783   | 0.8844  | 0.5173   | 0.001  |
| 0.162         | 16.0  | 8576  | 0.1305          | 0.8188   | 0.7530   | 0.8764  | 0.5202   | 0.001  |
| 0.1548        | 17.0  | 9112  | 0.1242          | 0.8291   | 0.7887   | 0.8945  | 0.5248   | 0.001  |
| 0.1532        | 18.0  | 9648  | 0.1247          | 0.8292   | 0.7823   | 0.8934  | 0.5227   | 0.001  |
| 0.152         | 19.0  | 10184 | 0.1272          | 0.8238   | 0.7688   | 0.8832  | 0.5280   | 0.001  |
| 0.1479        | 20.0  | 10720 | 0.1239          | 0.8280   | 0.7783   | 0.8834  | 0.5288   | 0.001  |
| 0.1483        | 21.0  | 11256 | 0.1376          | 0.8361   | 0.7914   | 0.8919  | 0.5341   | 0.001  |
| 0.1448        | 22.0  | 11792 | 0.1267          | 0.8292   | 0.7774   | 0.8842  | 0.5380   | 0.001  |
| 0.1456        | 23.0  | 12328 | 0.1217          | 0.8334   | 0.7914   | 0.8883  | 0.5448   | 0.001  |
| 0.1441        | 24.0  | 12864 | 0.1193          | 0.8283   | 0.7852   | 0.8801  | 0.5380   | 0.001  |
| 0.1406        | 25.0  | 13400 | 0.1185          | 0.8392   | 0.8020   | 0.8988  | 0.5341   | 0.001  |
| 0.1416        | 26.0  | 13936 | 0.1295          | 0.8351   | 0.7851   | 0.8889  | 0.5441   | 0.001  |
| 0.1417        | 27.0  | 14472 | 0.1390          | 0.8287   | 0.7699   | 0.8808  | 0.5305   | 0.001  |
| 0.142         | 28.0  | 15008 | 0.1256          | 0.8328   | 0.7857   | 0.8888  | 0.5441   | 0.001  |
| 0.14          | 29.0  | 15544 | 0.1268          | 0.8291   | 0.7759   | 0.8815  | 0.5359   | 0.001  |
| 0.1415        | 30.0  | 16080 | 0.1374          | 0.8240   | 0.7675   | 0.8722  | 0.5420   | 0.001  |
| 0.1414        | 31.0  | 16616 | 0.1281          | 0.8310   | 0.7795   | 0.8838  | 0.5406   | 0.001  |
| 0.1349        | 32.0  | 17152 | 0.1144          | 0.8389   | 0.7927   | 0.8892  | 0.5513   | 0.0001 |
| 0.1294        | 33.0  | 17688 | 0.1097          | 0.8414   | 0.7991   | 0.8915  | 0.5534   | 0.0001 |
| 0.1281        | 34.0  | 18224 | 0.1160          | 0.8425   | 0.7982   | 0.8925  | 0.5520   | 0.0001 |
| 0.1274        | 35.0  | 18760 | 0.1244          | 0.8441   | 0.7999   | 0.8935  | 0.5577   | 0.0001 |
| 0.1243        | 36.0  | 19296 | 0.1100          | 0.8434   | 0.7991   | 0.8898  | 0.5559   | 0.0001 |
| 0.1231        | 37.0  | 19832 | 0.1073          | 0.8485   | 0.8086   | 0.8989  | 0.5641   | 0.0001 |
| 0.1245        | 38.0  | 20368 | 0.1092          | 0.8456   | 0.8054   | 0.8916  | 0.5602   | 0.0001 |
| 0.1197        | 39.0  | 20904 | 0.1069          | 0.8483   | 0.8112   | 0.9002  | 0.5623   | 0.0001 |
| 0.1242        | 40.0  | 21440 | 0.1065          | 0.8468   | 0.8081   | 0.8949  | 0.5638   | 0.0001 |
| 0.1167        | 41.0  | 21976 | 0.1083          | 0.8462   | 0.8043   | 0.8934  | 0.5591   | 0.0001 |
| 0.1179        | 42.0  | 22512 | 0.1072          | 0.8505   | 0.8090   | 0.8978  | 0.5691   | 0.0001 |
| 0.1186        | 43.0  | 23048 | 0.1179          | 0.8483   | 0.8072   | 0.8945  | 0.5613   | 0.0001 |
| 0.1174        | 44.0  | 23584 | 0.1068          | 0.8477   | 0.8080   | 0.8946  | 0.5656   | 0.0001 |
| 0.1153        | 45.0  | 24120 | 0.1047          | 0.8534   | 0.8193   | 0.9025  | 0.5716   | 0.0001 |
| 0.1167        | 46.0  | 24656 | 0.1062          | 0.8535   | 0.8229   | 0.9080  | 0.5666   | 0.0001 |
| 0.1162        | 47.0  | 25192 | 0.1060          | 0.8522   | 0.8180   | 0.9006  | 0.5695   | 0.0001 |
| 0.1145        | 48.0  | 25728 | 0.1041          | 0.8529   | 0.8154   | 0.9002  | 0.5745   | 0.0001 |
| 0.1143        | 49.0  | 26264 | 0.1033          | 0.8542   | 0.8182   | 0.9043  | 0.5652   | 0.0001 |
| 0.1129        | 50.0  | 26800 | 0.1054          | 0.8508   | 0.8102   | 0.8956  | 0.5720   | 0.0001 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1

{"language": ["eng"], "license": "apache-2.0", "tags": ["multilabel-image-classification", "multilabel", "generated_from_trainer"], "metrics": ["accuracy"], "base_model": "facebook/dinov2-large", "model-index": [{"name": "dino-large-2023_12_08-with_custom_head-imgsize1036", "results": []}]}
transformers pytorch dinov2 multilabel-image-classification multilabel generated_from_trainer eng base_model:facebook/dinov2-large license:apache-2.0 endpoints_compatible region:us