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# deit-base-distilled-patch16-224-85-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: 0.3071
- Accuracy: 0.9091

## 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        | 1.0   | 2    | 1.1685          | 0.3182   |
| No log        | 2.0   | 4    | 0.7295          | 0.4545   |
| No log        | 3.0   | 6    | 0.6641          | 0.7045   |
| No log        | 4.0   | 8    | 0.7703          | 0.7045   |
| 0.7885        | 5.0   | 10   | 0.6750          | 0.7045   |
| 0.7885        | 6.0   | 12   | 0.6446          | 0.7045   |
| 0.7885        | 7.0   | 14   | 0.6919          | 0.7045   |
| 0.7885        | 8.0   | 16   | 0.6489          | 0.7045   |
| 0.7885        | 9.0   | 18   | 0.5245          | 0.7273   |
| 0.4488        | 10.0  | 20   | 0.8494          | 0.7045   |
| 0.4488        | 11.0  | 22   | 0.9086          | 0.6818   |
| 0.4488        | 12.0  | 24   | 0.5250          | 0.75     |
| 0.4488        | 13.0  | 26   | 0.5179          | 0.7727   |
| 0.4488        | 14.0  | 28   | 0.4423          | 0.7727   |
| 0.3387        | 15.0  | 30   | 0.5114          | 0.7273   |
| 0.3387        | 16.0  | 32   | 0.5048          | 0.75     |
| 0.3387        | 17.0  | 34   | 0.4997          | 0.7045   |
| 0.3387        | 18.0  | 36   | 0.4776          | 0.7045   |
| 0.3387        | 19.0  | 38   | 0.4138          | 0.7955   |
| 0.24          | 20.0  | 40   | 0.3220          | 0.8864   |
| 0.24          | 21.0  | 42   | 0.3363          | 0.8409   |
| 0.24          | 22.0  | 44   | 0.2958          | 0.8636   |
| 0.24          | 23.0  | 46   | 0.3098          | 0.8636   |
| 0.24          | 24.0  | 48   | 0.4030          | 0.8636   |
| 0.1524        | 25.0  | 50   | 0.3094          | 0.8636   |
| 0.1524        | 26.0  | 52   | 0.2721          | 0.8864   |
| 0.1524        | 27.0  | 54   | 0.3363          | 0.8636   |
| 0.1524        | 28.0  | 56   | 0.2731          | 0.8636   |
| 0.1524        | 29.0  | 58   | 0.5660          | 0.7955   |
| 0.1646        | 30.0  | 60   | 0.4949          | 0.8409   |
| 0.1646        | 31.0  | 62   | 0.4087          | 0.7727   |
| 0.1646        | 32.0  | 64   | 0.4467          | 0.8409   |
| 0.1646        | 33.0  | 66   | 0.4130          | 0.8182   |
| 0.1646        | 34.0  | 68   | 0.3727          | 0.8409   |
| 0.136         | 35.0  | 70   | 0.5894          | 0.7727   |
| 0.136         | 36.0  | 72   | 0.9462          | 0.75     |
| 0.136         | 37.0  | 74   | 0.5926          | 0.7273   |
| 0.136         | 38.0  | 76   | 0.3138          | 0.8864   |
| 0.136         | 39.0  | 78   | 0.4173          | 0.8864   |
| 0.163         | 40.0  | 80   | 0.3154          | 0.8636   |
| 0.163         | 41.0  | 82   | 0.3235          | 0.8636   |
| 0.163         | 42.0  | 84   | 0.3902          | 0.8182   |
| 0.163         | 43.0  | 86   | 0.3699          | 0.7955   |
| 0.163         | 44.0  | 88   | 0.4311          | 0.8182   |
| 0.1018        | 45.0  | 90   | 0.3071          | 0.9091   |
| 0.1018        | 46.0  | 92   | 0.2849          | 0.9091   |
| 0.1018        | 47.0  | 94   | 0.3226          | 0.8409   |
| 0.1018        | 48.0  | 96   | 0.2967          | 0.8409   |
| 0.1018        | 49.0  | 98   | 0.2936          | 0.8636   |
| 0.0957        | 50.0  | 100  | 0.2737          | 0.8864   |
| 0.0957        | 51.0  | 102  | 0.2845          | 0.8864   |
| 0.0957        | 52.0  | 104  | 0.3300          | 0.8409   |
| 0.0957        | 53.0  | 106  | 0.4029          | 0.8409   |
| 0.0957        | 54.0  | 108  | 0.4279          | 0.8182   |
| 0.1036        | 55.0  | 110  | 0.3900          | 0.8182   |
| 0.1036        | 56.0  | 112  | 0.4038          | 0.8636   |
| 0.1036        | 57.0  | 114  | 0.3569          | 0.8409   |
| 0.1036        | 58.0  | 116  | 0.5611          | 0.8182   |
| 0.1036        | 59.0  | 118  | 0.6900          | 0.8182   |
| 0.1048        | 60.0  | 120  | 0.5679          | 0.8182   |
| 0.1048        | 61.0  | 122  | 0.4567          | 0.8182   |
| 0.1048        | 62.0  | 124  | 0.3815          | 0.7955   |
| 0.1048        | 63.0  | 126  | 0.3546          | 0.7955   |
| 0.1048        | 64.0  | 128  | 0.3654          | 0.7955   |
| 0.0928        | 65.0  | 130  | 0.3337          | 0.8864   |
| 0.0928        | 66.0  | 132  | 0.4161          | 0.8409   |
| 0.0928        | 67.0  | 134  | 0.3615          | 0.8409   |
| 0.0928        | 68.0  | 136  | 0.4061          | 0.8182   |
| 0.0928        | 69.0  | 138  | 0.4191          | 0.8182   |
| 0.1091        | 70.0  | 140  | 0.3978          | 0.7955   |
| 0.1091        | 71.0  | 142  | 0.5168          | 0.75     |
| 0.1091        | 72.0  | 144  | 0.5268          | 0.75     |
| 0.1091        | 73.0  | 146  | 0.5667          | 0.7955   |
| 0.1091        | 74.0  | 148  | 0.5396          | 0.7727   |
| 0.1009        | 75.0  | 150  | 0.4807          | 0.75     |
| 0.1009        | 76.0  | 152  | 0.3957          | 0.8182   |
| 0.1009        | 77.0  | 154  | 0.3519          | 0.8636   |
| 0.1009        | 78.0  | 156  | 0.3654          | 0.8636   |
| 0.1009        | 79.0  | 158  | 0.3577          | 0.8409   |
| 0.0836        | 80.0  | 160  | 0.3216          | 0.8636   |
| 0.0836        | 81.0  | 162  | 0.3132          | 0.8409   |
| 0.0836        | 82.0  | 164  | 0.3003          | 0.8636   |
| 0.0836        | 83.0  | 166  | 0.3024          | 0.8636   |
| 0.0836        | 84.0  | 168  | 0.3214          | 0.8409   |
| 0.0928        | 85.0  | 170  | 0.3306          | 0.8182   |
| 0.0928        | 86.0  | 172  | 0.3284          | 0.8409   |
| 0.0928        | 87.0  | 174  | 0.3272          | 0.8182   |
| 0.0928        | 88.0  | 176  | 0.3261          | 0.8182   |
| 0.0928        | 89.0  | 178  | 0.3099          | 0.8409   |
| 0.0915        | 90.0  | 180  | 0.2928          | 0.8409   |
| 0.0915        | 91.0  | 182  | 0.2848          | 0.8409   |
| 0.0915        | 92.0  | 184  | 0.2827          | 0.8409   |
| 0.0915        | 93.0  | 186  | 0.2885          | 0.8636   |
| 0.0915        | 94.0  | 188  | 0.3084          | 0.8864   |
| 0.0775        | 95.0  | 190  | 0.3321          | 0.8409   |
| 0.0775        | 96.0  | 192  | 0.3358          | 0.8636   |
| 0.0775        | 97.0  | 194  | 0.3221          | 0.8409   |
| 0.0775        | 98.0  | 196  | 0.3096          | 0.8636   |
| 0.0775        | 99.0  | 198  | 0.3007          | 0.8864   |
| 0.091         | 100.0 | 200  | 0.2976          | 0.8864   |


### Framework versions

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

hasta normal