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# deit-base-distilled-patch16-224-85-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: 0.1991
- Accuracy: 0.9318

## 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    | 1.2745          | 0.2727   |
| No log        | 2.0   | 4    | 0.8028          | 0.4091   |
| No log        | 3.0   | 6    | 0.7456          | 0.7045   |
| No log        | 4.0   | 8    | 0.7982          | 0.7045   |
| 0.7325        | 5.0   | 10   | 0.6233          | 0.7045   |
| 0.7325        | 6.0   | 12   | 0.5093          | 0.7273   |
| 0.7325        | 7.0   | 14   | 0.5566          | 0.7045   |
| 0.7325        | 8.0   | 16   | 0.6839          | 0.7045   |
| 0.7325        | 9.0   | 18   | 0.4821          | 0.75     |
| 0.4472        | 10.0  | 20   | 0.4365          | 0.7727   |
| 0.4472        | 11.0  | 22   | 0.5158          | 0.7273   |
| 0.4472        | 12.0  | 24   | 0.4196          | 0.8182   |
| 0.4472        | 13.0  | 26   | 0.3599          | 0.8409   |
| 0.4472        | 14.0  | 28   | 0.3604          | 0.8636   |
| 0.3483        | 15.0  | 30   | 0.3634          | 0.8182   |
| 0.3483        | 16.0  | 32   | 0.2803          | 0.8864   |
| 0.3483        | 17.0  | 34   | 0.2592          | 0.8864   |
| 0.3483        | 18.0  | 36   | 0.2655          | 0.9091   |
| 0.3483        | 19.0  | 38   | 0.2333          | 0.8864   |
| 0.2514        | 20.0  | 40   | 0.2590          | 0.8636   |
| 0.2514        | 21.0  | 42   | 0.2642          | 0.8864   |
| 0.2514        | 22.0  | 44   | 0.2637          | 0.8864   |
| 0.2514        | 23.0  | 46   | 0.1991          | 0.9318   |
| 0.2514        | 24.0  | 48   | 0.1941          | 0.9091   |
| 0.1847        | 25.0  | 50   | 0.1868          | 0.8864   |
| 0.1847        | 26.0  | 52   | 0.1828          | 0.8864   |
| 0.1847        | 27.0  | 54   | 0.1711          | 0.8864   |
| 0.1847        | 28.0  | 56   | 0.2423          | 0.8864   |
| 0.1847        | 29.0  | 58   | 0.2162          | 0.8864   |
| 0.1501        | 30.0  | 60   | 0.1854          | 0.9091   |
| 0.1501        | 31.0  | 62   | 0.3071          | 0.8636   |
| 0.1501        | 32.0  | 64   | 0.2435          | 0.8864   |
| 0.1501        | 33.0  | 66   | 0.1728          | 0.9091   |
| 0.1501        | 34.0  | 68   | 0.1644          | 0.9091   |
| 0.13          | 35.0  | 70   | 0.2768          | 0.8409   |
| 0.13          | 36.0  | 72   | 0.1539          | 0.9318   |
| 0.13          | 37.0  | 74   | 0.2580          | 0.9091   |
| 0.13          | 38.0  | 76   | 0.1783          | 0.8864   |
| 0.13          | 39.0  | 78   | 0.1782          | 0.8636   |
| 0.1357        | 40.0  | 80   | 0.2035          | 0.8864   |
| 0.1357        | 41.0  | 82   | 0.2117          | 0.8864   |
| 0.1357        | 42.0  | 84   | 0.1793          | 0.9091   |
| 0.1357        | 43.0  | 86   | 0.2002          | 0.9091   |
| 0.1357        | 44.0  | 88   | 0.2366          | 0.8864   |
| 0.105         | 45.0  | 90   | 0.2008          | 0.9318   |
| 0.105         | 46.0  | 92   | 0.2368          | 0.8864   |
| 0.105         | 47.0  | 94   | 0.2142          | 0.8864   |
| 0.105         | 48.0  | 96   | 0.2117          | 0.8864   |
| 0.105         | 49.0  | 98   | 0.2621          | 0.8864   |
| 0.1091        | 50.0  | 100  | 0.2231          | 0.8864   |
| 0.1091        | 51.0  | 102  | 0.1946          | 0.9318   |
| 0.1091        | 52.0  | 104  | 0.2001          | 0.9318   |
| 0.1091        | 53.0  | 106  | 0.2031          | 0.9091   |
| 0.1091        | 54.0  | 108  | 0.2078          | 0.9091   |
| 0.1054        | 55.0  | 110  | 0.2250          | 0.9091   |
| 0.1054        | 56.0  | 112  | 0.2180          | 0.9091   |
| 0.1054        | 57.0  | 114  | 0.1915          | 0.9318   |
| 0.1054        | 58.0  | 116  | 0.2227          | 0.8864   |
| 0.1054        | 59.0  | 118  | 0.2352          | 0.8864   |
| 0.0982        | 60.0  | 120  | 0.2329          | 0.8864   |
| 0.0982        | 61.0  | 122  | 0.2135          | 0.9091   |
| 0.0982        | 62.0  | 124  | 0.1949          | 0.8864   |
| 0.0982        | 63.0  | 126  | 0.2149          | 0.9318   |
| 0.0982        | 64.0  | 128  | 0.2435          | 0.9091   |
| 0.0808        | 65.0  | 130  | 0.2541          | 0.9091   |
| 0.0808        | 66.0  | 132  | 0.2447          | 0.9091   |
| 0.0808        | 67.0  | 134  | 0.1904          | 0.9318   |
| 0.0808        | 68.0  | 136  | 0.2437          | 0.9091   |
| 0.0808        | 69.0  | 138  | 0.3593          | 0.8864   |
| 0.0843        | 70.0  | 140  | 0.4187          | 0.8864   |
| 0.0843        | 71.0  | 142  | 0.3510          | 0.8864   |
| 0.0843        | 72.0  | 144  | 0.2315          | 0.9091   |
| 0.0843        | 73.0  | 146  | 0.2049          | 0.9091   |
| 0.0843        | 74.0  | 148  | 0.2150          | 0.9091   |
| 0.0942        | 75.0  | 150  | 0.2116          | 0.9091   |
| 0.0942        | 76.0  | 152  | 0.2014          | 0.9091   |
| 0.0942        | 77.0  | 154  | 0.2198          | 0.9091   |
| 0.0942        | 78.0  | 156  | 0.2538          | 0.9318   |
| 0.0942        | 79.0  | 158  | 0.2755          | 0.9318   |
| 0.0884        | 80.0  | 160  | 0.2491          | 0.9091   |
| 0.0884        | 81.0  | 162  | 0.2100          | 0.9091   |
| 0.0884        | 82.0  | 164  | 0.1977          | 0.9091   |
| 0.0884        | 83.0  | 166  | 0.1979          | 0.9091   |
| 0.0884        | 84.0  | 168  | 0.2145          | 0.9091   |
| 0.0637        | 85.0  | 170  | 0.2192          | 0.9091   |
| 0.0637        | 86.0  | 172  | 0.2055          | 0.9318   |
| 0.0637        | 87.0  | 174  | 0.1994          | 0.9318   |
| 0.0637        | 88.0  | 176  | 0.1975          | 0.9091   |
| 0.0637        | 89.0  | 178  | 0.1974          | 0.9091   |
| 0.0923        | 90.0  | 180  | 0.1965          | 0.9091   |
| 0.0923        | 91.0  | 182  | 0.1925          | 0.9091   |
| 0.0923        | 92.0  | 184  | 0.1942          | 0.9091   |
| 0.0923        | 93.0  | 186  | 0.1969          | 0.9318   |
| 0.0923        | 94.0  | 188  | 0.1949          | 0.9318   |
| 0.0657        | 95.0  | 190  | 0.1904          | 0.9318   |
| 0.0657        | 96.0  | 192  | 0.1877          | 0.9091   |
| 0.0657        | 97.0  | 194  | 0.1885          | 0.9091   |
| 0.0657        | 98.0  | 196  | 0.1902          | 0.9318   |
| 0.0657        | 99.0  | 198  | 0.1922          | 0.9318   |
| 0.0822        | 100.0 | 200  | 0.1932          | 0.9318   |


### Framework versions

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

hasta normal