
<!-- 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. -->

# dino-base-2023_11_27-with_custom_head

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the multilabel_complete_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1028
- F1 Micro: 0.8515
- F1 Macro: 0.8179
- Roc Auc: 0.9057
- Accuracy: 0.5716
- 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: 0.01
- 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: 90

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:------:|
| 0.2471        | 1.0   | 536   | 0.2136          | 0.5684   | 0.4006   | 0.7020  | 0.3944   | 0.01   |
| 0.2208        | 2.0   | 1072  | 0.2199          | 0.6909   | 0.6462   | 0.7945  | 0.4091   | 0.01   |
| 0.2181        | 3.0   | 1608  | 0.1979          | 0.6712   | 0.5771   | 0.7667  | 0.4312   | 0.01   |
| 0.2187        | 4.0   | 2144  | 0.1767          | 0.7318   | 0.6061   | 0.8269  | 0.4137   | 0.01   |
| 0.2128        | 5.0   | 2680  | 0.1760          | 0.7173   | 0.5527   | 0.8012  | 0.4327   | 0.01   |
| 0.2171        | 6.0   | 3216  | 0.1992          | 0.7109   | 0.5184   | 0.8062  | 0.4227   | 0.01   |
| 0.2108        | 7.0   | 3752  | 0.1695          | 0.7339   | 0.6055   | 0.8232  | 0.4173   | 0.01   |
| 0.2147        | 8.0   | 4288  | 0.1619          | 0.7441   | 0.6176   | 0.8342  | 0.4227   | 0.01   |
| 0.2112        | 9.0   | 4824  | 0.1708          | 0.7337   | 0.6402   | 0.8245  | 0.4309   | 0.01   |
| 0.216         | 10.0  | 5360  | 0.1751          | 0.7493   | 0.6434   | 0.8372  | 0.4284   | 0.01   |
| 0.2151        | 11.0  | 5896  | 0.1701          | 0.7242   | 0.6293   | 0.8078  | 0.4337   | 0.01   |
| 0.213         | 12.0  | 6432  | 0.2409          | 0.6629   | 0.5371   | 0.8035  | 0.3566   | 0.01   |
| 0.2161        | 13.0  | 6968  | 0.1705          | 0.7291   | 0.6243   | 0.8207  | 0.4194   | 0.01   |
| 0.2136        | 14.0  | 7504  | 0.1693          | 0.7343   | 0.6215   | 0.8177  | 0.4427   | 0.01   |
| 0.1826        | 15.0  | 8040  | 0.1388          | 0.7968   | 0.7460   | 0.8648  | 0.4970   | 0.001  |
| 0.1731        | 16.0  | 8576  | 0.1476          | 0.8016   | 0.7385   | 0.8631  | 0.5155   | 0.001  |
| 0.1649        | 17.0  | 9112  | 0.1351          | 0.8133   | 0.7693   | 0.8812  | 0.5023   | 0.001  |
| 0.1624        | 18.0  | 9648  | 0.1385          | 0.8186   | 0.7714   | 0.8838  | 0.5213   | 0.001  |
| 0.1576        | 19.0  | 10184 | 0.1302          | 0.8176   | 0.7632   | 0.8779  | 0.5205   | 0.001  |
| 0.1544        | 20.0  | 10720 | 0.1234          | 0.8230   | 0.7722   | 0.8781  | 0.5320   | 0.001  |
| 0.1542        | 21.0  | 11256 | 0.1304          | 0.8268   | 0.7755   | 0.8884  | 0.5259   | 0.001  |
| 0.1525        | 22.0  | 11792 | 0.1220          | 0.8177   | 0.7646   | 0.8725  | 0.5377   | 0.001  |
| 0.1505        | 23.0  | 12328 | 0.1311          | 0.8264   | 0.7872   | 0.8918  | 0.5255   | 0.001  |
| 0.1515        | 24.0  | 12864 | 0.1247          | 0.8188   | 0.7630   | 0.8737  | 0.5316   | 0.001  |
| 0.1471        | 25.0  | 13400 | 0.1265          | 0.8258   | 0.7726   | 0.8875  | 0.5227   | 0.001  |
| 0.1475        | 26.0  | 13936 | 0.1277          | 0.8301   | 0.7834   | 0.8867  | 0.5330   | 0.001  |
| 0.1484        | 27.0  | 14472 | 0.1236          | 0.8218   | 0.7661   | 0.8754  | 0.5398   | 0.001  |
| 0.1472        | 28.0  | 15008 | 0.1257          | 0.8229   | 0.7729   | 0.8758  | 0.5402   | 0.001  |
| 0.1379        | 29.0  | 15544 | 0.1199          | 0.8352   | 0.7891   | 0.8865  | 0.5452   | 0.0001 |
| 0.1349        | 30.0  | 16080 | 0.1156          | 0.8413   | 0.7944   | 0.8951  | 0.5488   | 0.0001 |
| 0.1326        | 31.0  | 16616 | 0.1152          | 0.8404   | 0.7983   | 0.8961  | 0.5498   | 0.0001 |
| 0.1321        | 32.0  | 17152 | 0.1137          | 0.8386   | 0.7911   | 0.8902  | 0.5509   | 0.0001 |
| 0.1294        | 33.0  | 17688 | 0.1136          | 0.8406   | 0.7924   | 0.8916  | 0.5513   | 0.0001 |
| 0.1297        | 34.0  | 18224 | 0.1100          | 0.8439   | 0.7995   | 0.8965  | 0.5552   | 0.0001 |
| 0.1296        | 35.0  | 18760 | 0.1102          | 0.8431   | 0.7959   | 0.8953  | 0.5570   | 0.0001 |
| 0.1276        | 36.0  | 19296 | 0.1104          | 0.8429   | 0.7954   | 0.8933  | 0.5584   | 0.0001 |
| 0.1264        | 37.0  | 19832 | 0.1111          | 0.8468   | 0.8073   | 0.9004  | 0.5645   | 0.0001 |
| 0.1279        | 38.0  | 20368 | 0.1105          | 0.8457   | 0.8060   | 0.8964  | 0.5663   | 0.0001 |
| 0.1231        | 39.0  | 20904 | 0.1115          | 0.8481   | 0.8105   | 0.9016  | 0.5623   | 0.0001 |
| 0.1276        | 40.0  | 21440 | 0.1089          | 0.8443   | 0.7999   | 0.8932  | 0.5648   | 0.0001 |
| 0.121         | 41.0  | 21976 | 0.1098          | 0.8455   | 0.8015   | 0.8953  | 0.5627   | 0.0001 |
| 0.1229        | 42.0  | 22512 | 0.1087          | 0.8459   | 0.8009   | 0.8966  | 0.5620   | 0.0001 |
| 0.1227        | 43.0  | 23048 | 0.1088          | 0.8468   | 0.8067   | 0.8957  | 0.5688   | 0.0001 |
| 0.1221        | 44.0  | 23584 | 0.1076          | 0.8476   | 0.8066   | 0.8974  | 0.5673   | 0.0001 |
| 0.1191        | 45.0  | 24120 | 0.1069          | 0.8508   | 0.8173   | 0.9027  | 0.5698   | 0.0001 |
| 0.1212        | 46.0  | 24656 | 0.1072          | 0.8509   | 0.8174   | 0.9086  | 0.5634   | 0.0001 |
| 0.1198        | 47.0  | 25192 | 0.1066          | 0.8493   | 0.8090   | 0.9001  | 0.5688   | 0.0001 |
| 0.1201        | 48.0  | 25728 | 0.1076          | 0.8485   | 0.8083   | 0.9002  | 0.5652   | 0.0001 |
| 0.1189        | 49.0  | 26264 | 0.1065          | 0.8508   | 0.8152   | 0.9027  | 0.5688   | 0.0001 |
| 0.1176        | 50.0  | 26800 | 0.1073          | 0.8463   | 0.8034   | 0.8965  | 0.5634   | 0.0001 |
| 0.1202        | 51.0  | 27336 | 0.1073          | 0.8481   | 0.8102   | 0.8994  | 0.5727   | 0.0001 |
| 0.1167        | 52.0  | 27872 | 0.1060          | 0.8522   | 0.8179   | 0.9069  | 0.5716   | 0.0001 |
| 0.1192        | 53.0  | 28408 | 0.1063          | 0.8507   | 0.8128   | 0.9010  | 0.5713   | 0.0001 |
| 0.1156        | 54.0  | 28944 | 0.1067          | 0.8493   | 0.8113   | 0.9000  | 0.5720   | 0.0001 |
| 0.1193        | 55.0  | 29480 | 0.1069          | 0.8490   | 0.8116   | 0.8995  | 0.5727   | 0.0001 |
| 0.116         | 56.0  | 30016 | 0.1056          | 0.8543   | 0.8186   | 0.9077  | 0.5745   | 0.0001 |
| 0.1147        | 57.0  | 30552 | 0.1063          | 0.8505   | 0.8114   | 0.8980  | 0.5731   | 0.0001 |
| 0.1139        | 58.0  | 31088 | 0.1066          | 0.8489   | 0.8074   | 0.8986  | 0.5706   | 0.0001 |
| 0.1143        | 59.0  | 31624 | 0.1074          | 0.8491   | 0.8065   | 0.8971  | 0.5727   | 0.0001 |
| 0.1148        | 60.0  | 32160 | 0.1078          | 0.8499   | 0.8080   | 0.8981  | 0.5695   | 0.0001 |
| 0.1143        | 61.0  | 32696 | 0.1054          | 0.8512   | 0.8159   | 0.9010  | 0.5723   | 0.0001 |
| 0.1133        | 62.0  | 33232 | 0.1058          | 0.8496   | 0.8083   | 0.8973  | 0.5738   | 0.0001 |
| 0.1134        | 63.0  | 33768 | 0.1063          | 0.8479   | 0.8088   | 0.8991  | 0.5681   | 0.0001 |
| 0.1123        | 64.0  | 34304 | 0.1054          | 0.8504   | 0.8121   | 0.8997  | 0.5702   | 0.0001 |
| 0.1141        | 65.0  | 34840 | 0.1050          | 0.8494   | 0.8099   | 0.8989  | 0.5731   | 0.0001 |
| 0.1104        | 66.0  | 35376 | 0.1050          | 0.8507   | 0.8133   | 0.8979  | 0.5763   | 0.0001 |
| 0.1124        | 67.0  | 35912 | 0.1060          | 0.8513   | 0.8163   | 0.9036  | 0.5670   | 0.0001 |
| 0.1111        | 68.0  | 36448 | 0.1054          | 0.8512   | 0.8157   | 0.9019  | 0.5681   | 0.0001 |
| 0.1097        | 69.0  | 36984 | 0.1056          | 0.8501   | 0.8110   | 0.9021  | 0.5673   | 0.0001 |
| 0.1096        | 70.0  | 37520 | 0.1059          | 0.8501   | 0.8119   | 0.8997  | 0.5673   | 0.0001 |
| 0.1097        | 71.0  | 38056 | 0.1055          | 0.8517   | 0.8172   | 0.9037  | 0.5738   | 0.0001 |
| 0.1084        | 72.0  | 38592 | 0.1074          | 0.8469   | 0.8063   | 0.8961  | 0.5631   | 1e-05  |
| 0.1091        | 73.0  | 39128 | 0.1044          | 0.8525   | 0.8171   | 0.9028  | 0.5734   | 1e-05  |
| 0.1051        | 74.0  | 39664 | 0.1041          | 0.8533   | 0.8187   | 0.9050  | 0.5716   | 1e-05  |
| 0.1069        | 75.0  | 40200 | 0.1056          | 0.8506   | 0.8155   | 0.9013  | 0.5698   | 1e-05  |
| 0.1079        | 76.0  | 40736 | 0.1043          | 0.8517   | 0.8154   | 0.9027  | 0.5723   | 1e-05  |
| 0.1072        | 77.0  | 41272 | 0.1040          | 0.8536   | 0.8188   | 0.9026  | 0.5781   | 1e-05  |
| 0.105         | 78.0  | 41808 | 0.1043          | 0.8514   | 0.8150   | 0.9018  | 0.5713   | 1e-05  |
| 0.1061        | 79.0  | 42344 | 0.1043          | 0.8526   | 0.8181   | 0.9023  | 0.5734   | 1e-05  |
| 0.1045        | 80.0  | 42880 | 0.1051          | 0.8512   | 0.8177   | 0.9018  | 0.5720   | 1e-05  |
| 0.1062        | 81.0  | 43416 | 0.1069          | 0.8501   | 0.8157   | 0.8985  | 0.5695   | 1e-05  |
| 0.1057        | 82.0  | 43952 | 0.1040          | 0.8530   | 0.8184   | 0.9039  | 0.5734   | 1e-05  |
| 0.1073        | 83.0  | 44488 | 0.1048          | 0.8504   | 0.8151   | 0.8974  | 0.5713   | 1e-05  |
| 0.1059        | 84.0  | 45024 | 0.1044          | 0.8526   | 0.8178   | 0.9026  | 0.5741   | 1e-05  |
| 0.1054        | 85.0  | 45560 | 0.1063          | 0.8505   | 0.8149   | 0.9003  | 0.5702   | 1e-05  |
| 0.1046        | 86.0  | 46096 | 0.1043          | 0.8525   | 0.8161   | 0.9004  | 0.5727   | 1e-05  |
| 0.105         | 87.0  | 46632 | 0.1047          | 0.8532   | 0.8185   | 0.9042  | 0.5720   | 1e-05  |
| 0.1029        | 88.0  | 47168 | 0.1043          | 0.8518   | 0.8156   | 0.9041  | 0.5759   | 1e-05  |
| 0.1059        | 89.0  | 47704 | 0.1040          | 0.8539   | 0.8178   | 0.9034  | 0.5788   | 0.0000 |
| 0.1047        | 90.0  | 48240 | 0.1047          | 0.8505   | 0.8136   | 0.8983  | 0.5695   | 0.0000 |


### 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-base", "model-index": [{"name": "dino-base-2023_11_27-with_custom_head", "results": []}]}
transformers pytorch dinov2 multilabel-image-classification multilabel generated_from_trainer eng base_model:facebook/dinov2-base license:apache-2.0 endpoints_compatible has_space region:us