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# deit-base-distilled-patch16-224-55-fold4

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: 0.4908
- Accuracy: 0.8354

## 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        | 0.8571  | 3    | 0.8297          | 0.5063   |
| No log        | 2.0     | 7    | 0.6548          | 0.6203   |
| 0.6826        | 2.8571  | 10   | 0.6513          | 0.5190   |
| 0.6826        | 4.0     | 14   | 0.6024          | 0.7342   |
| 0.6826        | 4.8571  | 17   | 0.6473          | 0.5823   |
| 0.6198        | 6.0     | 21   | 0.5717          | 0.6835   |
| 0.6198        | 6.8571  | 24   | 0.7837          | 0.5570   |
| 0.6198        | 8.0     | 28   | 0.5272          | 0.7595   |
| 0.5409        | 8.8571  | 31   | 0.5162          | 0.7342   |
| 0.5409        | 10.0    | 35   | 0.6156          | 0.6709   |
| 0.5409        | 10.8571 | 38   | 0.5844          | 0.6582   |
| 0.5177        | 12.0    | 42   | 0.7013          | 0.6709   |
| 0.5177        | 12.8571 | 45   | 0.5017          | 0.7722   |
| 0.5177        | 14.0    | 49   | 0.4723          | 0.7975   |
| 0.4995        | 14.8571 | 52   | 0.7057          | 0.6835   |
| 0.4995        | 16.0    | 56   | 0.4669          | 0.8228   |
| 0.4995        | 16.8571 | 59   | 0.5737          | 0.7468   |
| 0.3767        | 18.0    | 63   | 0.5035          | 0.8101   |
| 0.3767        | 18.8571 | 66   | 0.8993          | 0.6203   |
| 0.3602        | 20.0    | 70   | 0.5425          | 0.7975   |
| 0.3602        | 20.8571 | 73   | 0.5605          | 0.7722   |
| 0.3602        | 22.0    | 77   | 0.4260          | 0.7975   |
| 0.3479        | 22.8571 | 80   | 0.4117          | 0.8228   |
| 0.3479        | 24.0    | 84   | 0.4017          | 0.7975   |
| 0.3479        | 24.8571 | 87   | 0.4401          | 0.8228   |
| 0.2845        | 26.0    | 91   | 0.4490          | 0.7975   |
| 0.2845        | 26.8571 | 94   | 0.5080          | 0.8101   |
| 0.2845        | 28.0    | 98   | 0.5014          | 0.7975   |
| 0.2316        | 28.8571 | 101  | 0.5385          | 0.7722   |
| 0.2316        | 30.0    | 105  | 0.5643          | 0.7595   |
| 0.2316        | 30.8571 | 108  | 0.4887          | 0.7848   |
| 0.2212        | 32.0    | 112  | 0.5253          | 0.7975   |
| 0.2212        | 32.8571 | 115  | 0.4633          | 0.7975   |
| 0.2212        | 34.0    | 119  | 0.5079          | 0.8228   |
| 0.2093        | 34.8571 | 122  | 0.5082          | 0.7975   |
| 0.2093        | 36.0    | 126  | 0.6113          | 0.7468   |
| 0.2093        | 36.8571 | 129  | 0.5094          | 0.7848   |
| 0.179         | 38.0    | 133  | 0.6253          | 0.8101   |
| 0.179         | 38.8571 | 136  | 0.5406          | 0.7848   |
| 0.173         | 40.0    | 140  | 0.6687          | 0.7722   |
| 0.173         | 40.8571 | 143  | 0.5691          | 0.7975   |
| 0.173         | 42.0    | 147  | 0.5776          | 0.7975   |
| 0.1881        | 42.8571 | 150  | 0.7816          | 0.7595   |
| 0.1881        | 44.0    | 154  | 0.4908          | 0.8354   |
| 0.1881        | 44.8571 | 157  | 0.5330          | 0.7848   |
| 0.161         | 46.0    | 161  | 0.5351          | 0.7848   |
| 0.161         | 46.8571 | 164  | 0.6663          | 0.7848   |
| 0.161         | 48.0    | 168  | 0.5382          | 0.7975   |
| 0.1446        | 48.8571 | 171  | 0.5877          | 0.7848   |
| 0.1446        | 50.0    | 175  | 0.6856          | 0.8228   |
| 0.1446        | 50.8571 | 178  | 0.6044          | 0.8101   |
| 0.1556        | 52.0    | 182  | 0.7954          | 0.7848   |
| 0.1556        | 52.8571 | 185  | 0.7432          | 0.7848   |
| 0.1556        | 54.0    | 189  | 0.7896          | 0.8101   |
| 0.1602        | 54.8571 | 192  | 0.8400          | 0.8101   |
| 0.1602        | 56.0    | 196  | 0.8243          | 0.7848   |
| 0.1602        | 56.8571 | 199  | 0.6864          | 0.8354   |
| 0.1357        | 58.0    | 203  | 0.7131          | 0.7722   |
| 0.1357        | 58.8571 | 206  | 0.9191          | 0.7722   |
| 0.1262        | 60.0    | 210  | 0.7465          | 0.7722   |
| 0.1262        | 60.8571 | 213  | 0.7127          | 0.7848   |
| 0.1262        | 62.0    | 217  | 0.6973          | 0.7975   |
| 0.1323        | 62.8571 | 220  | 0.7125          | 0.7848   |
| 0.1323        | 64.0    | 224  | 0.7235          | 0.7848   |
| 0.1323        | 64.8571 | 227  | 0.7200          | 0.7975   |
| 0.1258        | 66.0    | 231  | 0.7616          | 0.7848   |
| 0.1258        | 66.8571 | 234  | 0.8537          | 0.7848   |
| 0.1258        | 68.0    | 238  | 0.8223          | 0.7848   |
| 0.1316        | 68.8571 | 241  | 0.7751          | 0.8228   |
| 0.1316        | 70.0    | 245  | 0.7689          | 0.8228   |
| 0.1316        | 70.8571 | 248  | 0.7751          | 0.8101   |
| 0.1104        | 72.0    | 252  | 0.7770          | 0.8101   |
| 0.1104        | 72.8571 | 255  | 0.7916          | 0.7975   |
| 0.1104        | 74.0    | 259  | 0.7995          | 0.7848   |
| 0.1239        | 74.8571 | 262  | 0.7981          | 0.7848   |
| 0.1239        | 76.0    | 266  | 0.7890          | 0.8228   |
| 0.1239        | 76.8571 | 269  | 0.7888          | 0.8228   |
| 0.1057        | 78.0    | 273  | 0.7957          | 0.8228   |
| 0.1057        | 78.8571 | 276  | 0.7979          | 0.8228   |
| 0.1015        | 80.0    | 280  | 0.7959          | 0.8101   |
| 0.1015        | 80.8571 | 283  | 0.7935          | 0.8101   |
| 0.1015        | 82.0    | 287  | 0.7973          | 0.8228   |
| 0.101         | 82.8571 | 290  | 0.8033          | 0.7975   |
| 0.101         | 84.0    | 294  | 0.8072          | 0.7975   |
| 0.101         | 84.8571 | 297  | 0.8049          | 0.7975   |
| 0.1116        | 85.7143 | 300  | 0.8042          | 0.8101   |


### Framework versions

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

hasta normal