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# deit-base-distilled-patch16-224-65-fold2

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: 0.3095
- Accuracy: 0.9155

## 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    | 0.7211          | 0.4366   |
| No log        | 1.8462  | 6    | 0.7016          | 0.5070   |
| No log        | 2.7692  | 9    | 0.6703          | 0.6197   |
| 0.6946        | 4.0     | 13   | 0.6381          | 0.6620   |
| 0.6946        | 4.9231  | 16   | 0.5945          | 0.6761   |
| 0.6946        | 5.8462  | 19   | 0.6084          | 0.7183   |
| 0.6262        | 6.7692  | 22   | 0.5639          | 0.7465   |
| 0.6262        | 8.0     | 26   | 0.5203          | 0.7746   |
| 0.6262        | 8.9231  | 29   | 0.4805          | 0.7887   |
| 0.544         | 9.8462  | 32   | 0.5204          | 0.7324   |
| 0.544         | 10.7692 | 35   | 0.4635          | 0.7746   |
| 0.544         | 12.0    | 39   | 0.4957          | 0.7606   |
| 0.516         | 12.9231 | 42   | 0.4723          | 0.7746   |
| 0.516         | 13.8462 | 45   | 0.5170          | 0.7042   |
| 0.516         | 14.7692 | 48   | 0.5405          | 0.8169   |
| 0.4938        | 16.0    | 52   | 0.5082          | 0.7324   |
| 0.4938        | 16.9231 | 55   | 0.4608          | 0.7887   |
| 0.4938        | 17.8462 | 58   | 0.4211          | 0.7606   |
| 0.4123        | 18.7692 | 61   | 0.5015          | 0.7746   |
| 0.4123        | 20.0    | 65   | 0.3935          | 0.8592   |
| 0.4123        | 20.9231 | 68   | 0.4179          | 0.8169   |
| 0.3489        | 21.8462 | 71   | 0.3991          | 0.9014   |
| 0.3489        | 22.7692 | 74   | 0.3910          | 0.8592   |
| 0.3489        | 24.0    | 78   | 0.4277          | 0.8310   |
| 0.2889        | 24.9231 | 81   | 0.4032          | 0.8169   |
| 0.2889        | 25.8462 | 84   | 0.3703          | 0.8592   |
| 0.2889        | 26.7692 | 87   | 0.4404          | 0.8310   |
| 0.2659        | 28.0    | 91   | 0.3666          | 0.8592   |
| 0.2659        | 28.9231 | 94   | 0.3992          | 0.8169   |
| 0.2659        | 29.8462 | 97   | 0.4040          | 0.8169   |
| 0.2269        | 30.7692 | 100  | 0.3559          | 0.8592   |
| 0.2269        | 32.0    | 104  | 0.4766          | 0.8028   |
| 0.2269        | 32.9231 | 107  | 0.3852          | 0.8592   |
| 0.2031        | 33.8462 | 110  | 0.3702          | 0.8592   |
| 0.2031        | 34.7692 | 113  | 0.3203          | 0.8732   |
| 0.2031        | 36.0    | 117  | 0.5303          | 0.8169   |
| 0.2037        | 36.9231 | 120  | 0.3897          | 0.8732   |
| 0.2037        | 37.8462 | 123  | 0.3841          | 0.8732   |
| 0.2037        | 38.7692 | 126  | 0.3896          | 0.8873   |
| 0.2018        | 40.0    | 130  | 0.4177          | 0.8451   |
| 0.2018        | 40.9231 | 133  | 0.4548          | 0.8451   |
| 0.2018        | 41.8462 | 136  | 0.4115          | 0.8310   |
| 0.2018        | 42.7692 | 139  | 0.4121          | 0.8451   |
| 0.1721        | 44.0    | 143  | 0.3920          | 0.8592   |
| 0.1721        | 44.9231 | 146  | 0.3693          | 0.8451   |
| 0.1721        | 45.8462 | 149  | 0.3605          | 0.8592   |
| 0.1678        | 46.7692 | 152  | 0.5434          | 0.8310   |
| 0.1678        | 48.0    | 156  | 0.4189          | 0.8310   |
| 0.1678        | 48.9231 | 159  | 0.3124          | 0.8873   |
| 0.1604        | 49.8462 | 162  | 0.3293          | 0.8873   |
| 0.1604        | 50.7692 | 165  | 0.3372          | 0.9014   |
| 0.1604        | 52.0    | 169  | 0.3505          | 0.8732   |
| 0.1406        | 52.9231 | 172  | 0.3095          | 0.9155   |
| 0.1406        | 53.8462 | 175  | 0.3054          | 0.9155   |
| 0.1406        | 54.7692 | 178  | 0.3695          | 0.8873   |
| 0.1492        | 56.0    | 182  | 0.4058          | 0.8592   |
| 0.1492        | 56.9231 | 185  | 0.4650          | 0.8451   |
| 0.1492        | 57.8462 | 188  | 0.4060          | 0.8592   |
| 0.1359        | 58.7692 | 191  | 0.3819          | 0.8873   |
| 0.1359        | 60.0    | 195  | 0.5230          | 0.7887   |
| 0.1359        | 60.9231 | 198  | 0.4986          | 0.8169   |
| 0.1264        | 61.8462 | 201  | 0.4570          | 0.8310   |
| 0.1264        | 62.7692 | 204  | 0.4507          | 0.8451   |
| 0.1264        | 64.0    | 208  | 0.5765          | 0.8028   |
| 0.1478        | 64.9231 | 211  | 0.4514          | 0.8592   |
| 0.1478        | 65.8462 | 214  | 0.4434          | 0.8873   |
| 0.1478        | 66.7692 | 217  | 0.4403          | 0.8592   |
| 0.1398        | 68.0    | 221  | 0.5928          | 0.8310   |
| 0.1398        | 68.9231 | 224  | 0.4587          | 0.8592   |
| 0.1398        | 69.8462 | 227  | 0.4053          | 0.8451   |
| 0.161         | 70.7692 | 230  | 0.4233          | 0.8592   |
| 0.161         | 72.0    | 234  | 0.4264          | 0.8592   |
| 0.161         | 72.9231 | 237  | 0.4127          | 0.8310   |
| 0.1326        | 73.8462 | 240  | 0.4013          | 0.8592   |
| 0.1326        | 74.7692 | 243  | 0.4389          | 0.8451   |
| 0.1326        | 76.0    | 247  | 0.3772          | 0.8592   |
| 0.1236        | 76.9231 | 250  | 0.3600          | 0.8732   |
| 0.1236        | 77.8462 | 253  | 0.3890          | 0.8873   |
| 0.1236        | 78.7692 | 256  | 0.4401          | 0.8451   |
| 0.0973        | 80.0    | 260  | 0.4014          | 0.8592   |
| 0.0973        | 80.9231 | 263  | 0.3766          | 0.8732   |
| 0.0973        | 81.8462 | 266  | 0.3908          | 0.8451   |
| 0.0973        | 82.7692 | 269  | 0.4339          | 0.8592   |
| 0.1079        | 84.0    | 273  | 0.4567          | 0.8592   |
| 0.1079        | 84.9231 | 276  | 0.4415          | 0.8732   |
| 0.1079        | 85.8462 | 279  | 0.4183          | 0.8592   |
| 0.1015        | 86.7692 | 282  | 0.4039          | 0.8873   |
| 0.1015        | 88.0    | 286  | 0.3996          | 0.8873   |
| 0.1015        | 88.9231 | 289  | 0.4031          | 0.9014   |
| 0.1174        | 89.8462 | 292  | 0.4101          | 0.8732   |
| 0.1174        | 90.7692 | 295  | 0.4153          | 0.8732   |
| 0.1174        | 92.0    | 299  | 0.4146          | 0.8732   |
| 0.0968        | 92.3077 | 300  | 0.4145          | 0.8732   |


### Framework versions

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

hasta normal