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# deit-base-distilled-patch16-224-65-fold1

This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3816
- Accuracy: 0.8732

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9231  | 3    | 0.7888          | 0.4930   |
| No log        | 1.8462  | 6    | 0.7159          | 0.5070   |
| No log        | 2.7692  | 9    | 0.7091          | 0.5070   |
| 0.7703        | 4.0     | 13   | 0.6908          | 0.5352   |
| 0.7703        | 4.9231  | 16   | 0.6527          | 0.6197   |
| 0.7703        | 5.8462  | 19   | 0.6236          | 0.7324   |
| 0.6435        | 6.7692  | 22   | 0.6357          | 0.6901   |
| 0.6435        | 8.0     | 26   | 0.5442          | 0.7042   |
| 0.6435        | 8.9231  | 29   | 0.5449          | 0.7183   |
| 0.5366        | 9.8462  | 32   | 0.5124          | 0.7465   |
| 0.5366        | 10.7692 | 35   | 0.5029          | 0.7042   |
| 0.5366        | 12.0    | 39   | 0.5486          | 0.7183   |
| 0.4577        | 12.9231 | 42   | 0.5394          | 0.6761   |
| 0.4577        | 13.8462 | 45   | 0.5511          | 0.7465   |
| 0.4577        | 14.7692 | 48   | 0.5794          | 0.6901   |
| 0.4187        | 16.0    | 52   | 0.5368          | 0.7324   |
| 0.4187        | 16.9231 | 55   | 0.4678          | 0.7887   |
| 0.4187        | 17.8462 | 58   | 0.6597          | 0.7042   |
| 0.3542        | 18.7692 | 61   | 0.4969          | 0.8169   |
| 0.3542        | 20.0    | 65   | 0.7103          | 0.7324   |
| 0.3542        | 20.9231 | 68   | 0.4979          | 0.7606   |
| 0.3057        | 21.8462 | 71   | 0.5271          | 0.7324   |
| 0.3057        | 22.7692 | 74   | 0.5357          | 0.7746   |
| 0.3057        | 24.0    | 78   | 0.4847          | 0.7887   |
| 0.2816        | 24.9231 | 81   | 0.5425          | 0.8310   |
| 0.2816        | 25.8462 | 84   | 0.5239          | 0.8028   |
| 0.2816        | 26.7692 | 87   | 0.4141          | 0.8310   |
| 0.2881        | 28.0    | 91   | 0.4997          | 0.8028   |
| 0.2881        | 28.9231 | 94   | 0.4216          | 0.8028   |
| 0.2881        | 29.8462 | 97   | 0.4668          | 0.7887   |
| 0.2421        | 30.7692 | 100  | 0.5904          | 0.7887   |
| 0.2421        | 32.0    | 104  | 0.5240          | 0.7746   |
| 0.2421        | 32.9231 | 107  | 0.9937          | 0.7606   |
| 0.2402        | 33.8462 | 110  | 0.4989          | 0.8028   |
| 0.2402        | 34.7692 | 113  | 0.7232          | 0.7887   |
| 0.2402        | 36.0    | 117  | 0.4815          | 0.8451   |
| 0.1862        | 36.9231 | 120  | 0.7431          | 0.7746   |
| 0.1862        | 37.8462 | 123  | 0.4434          | 0.8028   |
| 0.1862        | 38.7692 | 126  | 0.4760          | 0.7887   |
| 0.1783        | 40.0    | 130  | 0.5006          | 0.7887   |
| 0.1783        | 40.9231 | 133  | 0.4986          | 0.7887   |
| 0.1783        | 41.8462 | 136  | 0.7947          | 0.7887   |
| 0.1783        | 42.7692 | 139  | 0.4897          | 0.8310   |
| 0.1685        | 44.0    | 143  | 0.7500          | 0.7606   |
| 0.1685        | 44.9231 | 146  | 0.6053          | 0.7887   |
| 0.1685        | 45.8462 | 149  | 0.4777          | 0.8169   |
| 0.1779        | 46.7692 | 152  | 0.5800          | 0.7746   |
| 0.1779        | 48.0    | 156  | 0.4681          | 0.8451   |
| 0.1779        | 48.9231 | 159  | 0.7729          | 0.8028   |
| 0.1502        | 49.8462 | 162  | 0.6487          | 0.8028   |
| 0.1502        | 50.7692 | 165  | 0.5224          | 0.8169   |
| 0.1502        | 52.0    | 169  | 0.7017          | 0.8028   |
| 0.1586        | 52.9231 | 172  | 0.6034          | 0.8028   |
| 0.1586        | 53.8462 | 175  | 0.5791          | 0.8028   |
| 0.1586        | 54.7692 | 178  | 0.5651          | 0.8169   |
| 0.134         | 56.0    | 182  | 0.4862          | 0.8028   |
| 0.134         | 56.9231 | 185  | 0.6751          | 0.8169   |
| 0.134         | 57.8462 | 188  | 0.5925          | 0.8169   |
| 0.1602        | 58.7692 | 191  | 0.3982          | 0.8451   |
| 0.1602        | 60.0    | 195  | 0.5969          | 0.7887   |
| 0.1602        | 60.9231 | 198  | 0.5721          | 0.7887   |
| 0.1217        | 61.8462 | 201  | 0.3816          | 0.8732   |
| 0.1217        | 62.7692 | 204  | 0.4110          | 0.8310   |
| 0.1217        | 64.0    | 208  | 0.6716          | 0.7887   |
| 0.1274        | 64.9231 | 211  | 0.3499          | 0.8732   |
| 0.1274        | 65.8462 | 214  | 0.3671          | 0.8169   |
| 0.1274        | 66.7692 | 217  | 0.5318          | 0.7887   |
| 0.1277        | 68.0    | 221  | 0.6734          | 0.7887   |
| 0.1277        | 68.9231 | 224  | 0.4726          | 0.8028   |
| 0.1277        | 69.8462 | 227  | 0.4311          | 0.8169   |
| 0.1232        | 70.7692 | 230  | 0.7072          | 0.7746   |
| 0.1232        | 72.0    | 234  | 0.5859          | 0.7887   |
| 0.1232        | 72.9231 | 237  | 0.3758          | 0.8310   |
| 0.1293        | 73.8462 | 240  | 0.3673          | 0.8451   |
| 0.1293        | 74.7692 | 243  | 0.3673          | 0.8592   |
| 0.1293        | 76.0    | 247  | 0.4752          | 0.8169   |
| 0.1117        | 76.9231 | 250  | 0.4450          | 0.8310   |
| 0.1117        | 77.8462 | 253  | 0.4437          | 0.8451   |
| 0.1117        | 78.7692 | 256  | 0.4330          | 0.8310   |
| 0.1092        | 80.0    | 260  | 0.5095          | 0.8169   |
| 0.1092        | 80.9231 | 263  | 0.4948          | 0.8169   |
| 0.1092        | 81.8462 | 266  | 0.4135          | 0.8592   |
| 0.1092        | 82.7692 | 269  | 0.4190          | 0.8451   |
| 0.1151        | 84.0    | 273  | 0.4194          | 0.8732   |
| 0.1151        | 84.9231 | 276  | 0.4356          | 0.8310   |
| 0.1151        | 85.8462 | 279  | 0.4623          | 0.8028   |
| 0.1085        | 86.7692 | 282  | 0.4845          | 0.8310   |
| 0.1085        | 88.0    | 286  | 0.4998          | 0.8169   |
| 0.1085        | 88.9231 | 289  | 0.5181          | 0.8028   |
| 0.0908        | 89.8462 | 292  | 0.5373          | 0.8169   |
| 0.0908        | 90.7692 | 295  | 0.5465          | 0.8169   |
| 0.0908        | 92.0    | 299  | 0.5422          | 0.8169   |
| 0.0902        | 92.3077 | 300  | 0.5417          | 0.8169   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

hasta normal