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# deit-base-distilled-patch16-224-65-fold5

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: 0.5156
- 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    | 0.7425          | 0.4930   |
| No log        | 1.8462  | 6    | 0.7193          | 0.5634   |
| No log        | 2.7692  | 9    | 0.6808          | 0.5915   |
| 0.7309        | 4.0     | 13   | 0.6253          | 0.5915   |
| 0.7309        | 4.9231  | 16   | 0.6022          | 0.6761   |
| 0.7309        | 5.8462  | 19   | 0.5589          | 0.6479   |
| 0.6449        | 6.7692  | 22   | 0.5559          | 0.7183   |
| 0.6449        | 8.0     | 26   | 0.4910          | 0.7183   |
| 0.6449        | 8.9231  | 29   | 0.4996          | 0.7606   |
| 0.5494        | 9.8462  | 32   | 0.4903          | 0.7324   |
| 0.5494        | 10.7692 | 35   | 0.7331          | 0.6620   |
| 0.5494        | 12.0    | 39   | 0.5053          | 0.6901   |
| 0.4793        | 12.9231 | 42   | 0.4781          | 0.7324   |
| 0.4793        | 13.8462 | 45   | 0.4997          | 0.7465   |
| 0.4793        | 14.7692 | 48   | 0.5197          | 0.7465   |
| 0.4327        | 16.0    | 52   | 0.5339          | 0.7606   |
| 0.4327        | 16.9231 | 55   | 0.4475          | 0.7606   |
| 0.4327        | 17.8462 | 58   | 0.4808          | 0.7887   |
| 0.3747        | 18.7692 | 61   | 0.4868          | 0.7465   |
| 0.3747        | 20.0    | 65   | 0.6206          | 0.7042   |
| 0.3747        | 20.9231 | 68   | 0.5271          | 0.7324   |
| 0.3474        | 21.8462 | 71   | 0.5227          | 0.6901   |
| 0.3474        | 22.7692 | 74   | 0.5078          | 0.7465   |
| 0.3474        | 24.0    | 78   | 0.5842          | 0.6901   |
| 0.267         | 24.9231 | 81   | 0.6015          | 0.7183   |
| 0.267         | 25.8462 | 84   | 0.6533          | 0.7606   |
| 0.267         | 26.7692 | 87   | 0.5764          | 0.7324   |
| 0.2333        | 28.0    | 91   | 0.4862          | 0.8028   |
| 0.2333        | 28.9231 | 94   | 0.6233          | 0.7183   |
| 0.2333        | 29.8462 | 97   | 0.7549          | 0.7465   |
| 0.2635        | 30.7692 | 100  | 0.4890          | 0.8028   |
| 0.2635        | 32.0    | 104  | 0.5616          | 0.8028   |
| 0.2635        | 32.9231 | 107  | 0.5501          | 0.7606   |
| 0.192         | 33.8462 | 110  | 0.4845          | 0.8169   |
| 0.192         | 34.7692 | 113  | 0.5116          | 0.7887   |
| 0.192         | 36.0    | 117  | 0.5017          | 0.8169   |
| 0.1763        | 36.9231 | 120  | 0.4798          | 0.7887   |
| 0.1763        | 37.8462 | 123  | 0.5328          | 0.7746   |
| 0.1763        | 38.7692 | 126  | 0.6393          | 0.7606   |
| 0.172         | 40.0    | 130  | 0.5481          | 0.7887   |
| 0.172         | 40.9231 | 133  | 0.5867          | 0.7887   |
| 0.172         | 41.8462 | 136  | 0.9223          | 0.7042   |
| 0.172         | 42.7692 | 139  | 0.6262          | 0.8028   |
| 0.1832        | 44.0    | 143  | 0.6091          | 0.7746   |
| 0.1832        | 44.9231 | 146  | 0.5837          | 0.7606   |
| 0.1832        | 45.8462 | 149  | 0.5465          | 0.7606   |
| 0.1641        | 46.7692 | 152  | 0.6745          | 0.7746   |
| 0.1641        | 48.0    | 156  | 0.5398          | 0.7887   |
| 0.1641        | 48.9231 | 159  | 0.5387          | 0.8169   |
| 0.1366        | 49.8462 | 162  | 0.5737          | 0.8028   |
| 0.1366        | 50.7692 | 165  | 0.5255          | 0.8310   |
| 0.1366        | 52.0    | 169  | 0.6486          | 0.7887   |
| 0.149         | 52.9231 | 172  | 0.5404          | 0.8169   |
| 0.149         | 53.8462 | 175  | 0.5655          | 0.8169   |
| 0.149         | 54.7692 | 178  | 0.6121          | 0.8028   |
| 0.1196        | 56.0    | 182  | 0.6182          | 0.8310   |
| 0.1196        | 56.9231 | 185  | 0.6175          | 0.8028   |
| 0.1196        | 57.8462 | 188  | 0.5921          | 0.8310   |
| 0.1202        | 58.7692 | 191  | 0.5953          | 0.8169   |
| 0.1202        | 60.0    | 195  | 0.6065          | 0.8028   |
| 0.1202        | 60.9231 | 198  | 0.5448          | 0.8310   |
| 0.1289        | 61.8462 | 201  | 0.5258          | 0.8451   |
| 0.1289        | 62.7692 | 204  | 0.5440          | 0.8310   |
| 0.1289        | 64.0    | 208  | 0.6082          | 0.8169   |
| 0.1262        | 64.9231 | 211  | 0.6358          | 0.8169   |
| 0.1262        | 65.8462 | 214  | 0.5982          | 0.8169   |
| 0.1262        | 66.7692 | 217  | 0.5850          | 0.8451   |
| 0.124         | 68.0    | 221  | 0.5733          | 0.8169   |
| 0.124         | 68.9231 | 224  | 0.5631          | 0.8028   |
| 0.124         | 69.8462 | 227  | 0.5375          | 0.8310   |
| 0.1208        | 70.7692 | 230  | 0.5158          | 0.8169   |
| 0.1208        | 72.0    | 234  | 0.5431          | 0.8169   |
| 0.1208        | 72.9231 | 237  | 0.5099          | 0.8451   |
| 0.1126        | 73.8462 | 240  | 0.5803          | 0.7887   |
| 0.1126        | 74.7692 | 243  | 0.5416          | 0.8028   |
| 0.1126        | 76.0    | 247  | 0.5835          | 0.8451   |
| 0.1089        | 76.9231 | 250  | 0.5923          | 0.8310   |
| 0.1089        | 77.8462 | 253  | 0.5228          | 0.8310   |
| 0.1089        | 78.7692 | 256  | 0.5467          | 0.8310   |
| 0.0965        | 80.0    | 260  | 0.5156          | 0.8732   |
| 0.0965        | 80.9231 | 263  | 0.5082          | 0.8451   |
| 0.0965        | 81.8462 | 266  | 0.5071          | 0.8451   |
| 0.0965        | 82.7692 | 269  | 0.5070          | 0.8592   |
| 0.0947        | 84.0    | 273  | 0.5268          | 0.8592   |
| 0.0947        | 84.9231 | 276  | 0.5283          | 0.8592   |
| 0.0947        | 85.8462 | 279  | 0.5261          | 0.8451   |
| 0.0751        | 86.7692 | 282  | 0.5286          | 0.8310   |
| 0.0751        | 88.0    | 286  | 0.5415          | 0.8310   |
| 0.0751        | 88.9231 | 289  | 0.5511          | 0.8310   |
| 0.0912        | 89.8462 | 292  | 0.5542          | 0.8310   |
| 0.0912        | 90.7692 | 295  | 0.5464          | 0.8310   |
| 0.0912        | 92.0    | 299  | 0.5410          | 0.8310   |
| 0.104         | 92.3077 | 300  | 0.5407          | 0.8310   |


### Framework versions

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

hasta normal