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# deit-base-distilled-patch16-224-65-fold3

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: 0.4993
- 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    | 0.7403          | 0.5493   |
| No log        | 1.8462  | 6    | 0.7199          | 0.5211   |
| No log        | 2.7692  | 9    | 0.7111          | 0.5634   |
| 0.7693        | 4.0     | 13   | 0.7015          | 0.5352   |
| 0.7693        | 4.9231  | 16   | 0.6471          | 0.6197   |
| 0.7693        | 5.8462  | 19   | 0.6691          | 0.6056   |
| 0.6542        | 6.7692  | 22   | 0.6188          | 0.6197   |
| 0.6542        | 8.0     | 26   | 0.6967          | 0.5775   |
| 0.6542        | 8.9231  | 29   | 0.5732          | 0.7324   |
| 0.5935        | 9.8462  | 32   | 0.5184          | 0.7042   |
| 0.5935        | 10.7692 | 35   | 0.6031          | 0.7183   |
| 0.5935        | 12.0    | 39   | 0.6671          | 0.6479   |
| 0.549         | 12.9231 | 42   | 0.5281          | 0.7183   |
| 0.549         | 13.8462 | 45   | 0.5792          | 0.7183   |
| 0.549         | 14.7692 | 48   | 0.5389          | 0.7465   |
| 0.4778        | 16.0    | 52   | 0.6010          | 0.7042   |
| 0.4778        | 16.9231 | 55   | 0.5245          | 0.7606   |
| 0.4778        | 17.8462 | 58   | 0.5491          | 0.7183   |
| 0.4039        | 18.7692 | 61   | 0.5590          | 0.7465   |
| 0.4039        | 20.0    | 65   | 0.4886          | 0.7324   |
| 0.4039        | 20.9231 | 68   | 0.5050          | 0.7324   |
| 0.3409        | 21.8462 | 71   | 0.4912          | 0.7465   |
| 0.3409        | 22.7692 | 74   | 0.4929          | 0.7746   |
| 0.3409        | 24.0    | 78   | 0.5365          | 0.7746   |
| 0.3202        | 24.9231 | 81   | 0.4685          | 0.8028   |
| 0.3202        | 25.8462 | 84   | 0.4404          | 0.8169   |
| 0.3202        | 26.7692 | 87   | 0.4639          | 0.8028   |
| 0.2466        | 28.0    | 91   | 0.5491          | 0.7606   |
| 0.2466        | 28.9231 | 94   | 0.5170          | 0.7606   |
| 0.2466        | 29.8462 | 97   | 0.4444          | 0.8028   |
| 0.2433        | 30.7692 | 100  | 0.4517          | 0.8310   |
| 0.2433        | 32.0    | 104  | 0.7797          | 0.7606   |
| 0.2433        | 32.9231 | 107  | 0.4321          | 0.8169   |
| 0.2535        | 33.8462 | 110  | 0.5956          | 0.7746   |
| 0.2535        | 34.7692 | 113  | 0.4695          | 0.7887   |
| 0.2535        | 36.0    | 117  | 0.8106          | 0.6901   |
| 0.2215        | 36.9231 | 120  | 0.7119          | 0.7465   |
| 0.2215        | 37.8462 | 123  | 0.4752          | 0.8028   |
| 0.2215        | 38.7692 | 126  | 0.4784          | 0.8169   |
| 0.2143        | 40.0    | 130  | 0.4773          | 0.8028   |
| 0.2143        | 40.9231 | 133  | 0.5581          | 0.8169   |
| 0.2143        | 41.8462 | 136  | 0.6098          | 0.8028   |
| 0.2143        | 42.7692 | 139  | 0.5193          | 0.8169   |
| 0.1726        | 44.0    | 143  | 0.4306          | 0.8451   |
| 0.1726        | 44.9231 | 146  | 0.4234          | 0.8592   |
| 0.1726        | 45.8462 | 149  | 0.5264          | 0.8169   |
| 0.1684        | 46.7692 | 152  | 0.7303          | 0.8028   |
| 0.1684        | 48.0    | 156  | 0.5079          | 0.8169   |
| 0.1684        | 48.9231 | 159  | 0.5392          | 0.8169   |
| 0.1604        | 49.8462 | 162  | 0.3951          | 0.8169   |
| 0.1604        | 50.7692 | 165  | 0.4311          | 0.8028   |
| 0.1604        | 52.0    | 169  | 0.4082          | 0.8028   |
| 0.1457        | 52.9231 | 172  | 0.4173          | 0.7887   |
| 0.1457        | 53.8462 | 175  | 0.4311          | 0.8310   |
| 0.1457        | 54.7692 | 178  | 0.4213          | 0.8028   |
| 0.1549        | 56.0    | 182  | 0.4713          | 0.8451   |
| 0.1549        | 56.9231 | 185  | 0.7493          | 0.8028   |
| 0.1549        | 57.8462 | 188  | 0.5161          | 0.8451   |
| 0.1391        | 58.7692 | 191  | 0.4685          | 0.8169   |
| 0.1391        | 60.0    | 195  | 0.6968          | 0.8028   |
| 0.1391        | 60.9231 | 198  | 0.5837          | 0.8310   |
| 0.1272        | 61.8462 | 201  | 0.5863          | 0.8169   |
| 0.1272        | 62.7692 | 204  | 0.5460          | 0.8310   |
| 0.1272        | 64.0    | 208  | 0.6198          | 0.8310   |
| 0.1341        | 64.9231 | 211  | 0.5584          | 0.8592   |
| 0.1341        | 65.8462 | 214  | 0.6429          | 0.8451   |
| 0.1341        | 66.7692 | 217  | 0.8592          | 0.8028   |
| 0.1144        | 68.0    | 221  | 0.8472          | 0.8028   |
| 0.1144        | 68.9231 | 224  | 0.8360          | 0.8169   |
| 0.1144        | 69.8462 | 227  | 0.6697          | 0.8169   |
| 0.1321        | 70.7692 | 230  | 0.6625          | 0.8028   |
| 0.1321        | 72.0    | 234  | 0.7228          | 0.8310   |
| 0.1321        | 72.9231 | 237  | 0.6793          | 0.8310   |
| 0.1206        | 73.8462 | 240  | 0.5571          | 0.8592   |
| 0.1206        | 74.7692 | 243  | 0.5106          | 0.8451   |
| 0.1206        | 76.0    | 247  | 0.6686          | 0.8310   |
| 0.131         | 76.9231 | 250  | 0.7132          | 0.8310   |
| 0.131         | 77.8462 | 253  | 0.5945          | 0.8451   |
| 0.131         | 78.7692 | 256  | 0.5516          | 0.7746   |
| 0.1009        | 80.0    | 260  | 0.5474          | 0.7606   |
| 0.1009        | 80.9231 | 263  | 0.5219          | 0.7887   |
| 0.1009        | 81.8462 | 266  | 0.5375          | 0.8451   |
| 0.1009        | 82.7692 | 269  | 0.5133          | 0.8451   |
| 0.1084        | 84.0    | 273  | 0.4911          | 0.8451   |
| 0.1084        | 84.9231 | 276  | 0.4993          | 0.8732   |
| 0.1084        | 85.8462 | 279  | 0.5418          | 0.8592   |
| 0.0851        | 86.7692 | 282  | 0.6010          | 0.8451   |
| 0.0851        | 88.0    | 286  | 0.6305          | 0.8451   |
| 0.0851        | 88.9231 | 289  | 0.6016          | 0.8451   |
| 0.1071        | 89.8462 | 292  | 0.5773          | 0.8592   |
| 0.1071        | 90.7692 | 295  | 0.5610          | 0.8732   |
| 0.1071        | 92.0    | 299  | 0.5522          | 0.8732   |
| 0.1139        | 92.3077 | 300  | 0.5514          | 0.8732   |


### Framework versions

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

hasta normal