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# deit-base-distilled-patch16-224-85-fold1

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: 0.2307
- Accuracy: 0.9545

## 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    | 1.1776          | 0.25     |
| No log        | 2.0   | 4    | 0.8165          | 0.3182   |
| No log        | 3.0   | 6    | 0.7525          | 0.7045   |
| No log        | 4.0   | 8    | 0.8074          | 0.7045   |
| 0.7495        | 5.0   | 10   | 0.6842          | 0.7045   |
| 0.7495        | 6.0   | 12   | 0.5606          | 0.6818   |
| 0.7495        | 7.0   | 14   | 0.5377          | 0.6818   |
| 0.7495        | 8.0   | 16   | 0.5761          | 0.7045   |
| 0.7495        | 9.0   | 18   | 0.5866          | 0.7045   |
| 0.4611        | 10.0  | 20   | 0.4894          | 0.7273   |
| 0.4611        | 11.0  | 22   | 0.6216          | 0.7273   |
| 0.4611        | 12.0  | 24   | 0.6272          | 0.7273   |
| 0.4611        | 13.0  | 26   | 0.4476          | 0.7727   |
| 0.4611        | 14.0  | 28   | 0.4451          | 0.75     |
| 0.3766        | 15.0  | 30   | 0.4370          | 0.7727   |
| 0.3766        | 16.0  | 32   | 0.4937          | 0.75     |
| 0.3766        | 17.0  | 34   | 0.4977          | 0.7955   |
| 0.3766        | 18.0  | 36   | 0.4551          | 0.8409   |
| 0.3766        | 19.0  | 38   | 0.3776          | 0.7727   |
| 0.3147        | 20.0  | 40   | 0.3347          | 0.8409   |
| 0.3147        | 21.0  | 42   | 0.5178          | 0.7727   |
| 0.3147        | 22.0  | 44   | 0.3430          | 0.8409   |
| 0.3147        | 23.0  | 46   | 0.3091          | 0.8409   |
| 0.3147        | 24.0  | 48   | 0.3995          | 0.8864   |
| 0.2176        | 25.0  | 50   | 0.2971          | 0.8409   |
| 0.2176        | 26.0  | 52   | 0.3137          | 0.8864   |
| 0.2176        | 27.0  | 54   | 0.2694          | 0.8864   |
| 0.2176        | 28.0  | 56   | 0.2589          | 0.8864   |
| 0.2176        | 29.0  | 58   | 0.3612          | 0.8636   |
| 0.1855        | 30.0  | 60   | 0.3406          | 0.8636   |
| 0.1855        | 31.0  | 62   | 0.4738          | 0.8864   |
| 0.1855        | 32.0  | 64   | 0.7612          | 0.7955   |
| 0.1855        | 33.0  | 66   | 0.5307          | 0.8864   |
| 0.1855        | 34.0  | 68   | 0.3346          | 0.8636   |
| 0.2006        | 35.0  | 70   | 0.3562          | 0.8409   |
| 0.2006        | 36.0  | 72   | 0.5255          | 0.8409   |
| 0.2006        | 37.0  | 74   | 0.3795          | 0.8409   |
| 0.2006        | 38.0  | 76   | 0.2924          | 0.9091   |
| 0.2006        | 39.0  | 78   | 0.2921          | 0.8864   |
| 0.161         | 40.0  | 80   | 0.3895          | 0.8409   |
| 0.161         | 41.0  | 82   | 0.3421          | 0.8182   |
| 0.161         | 42.0  | 84   | 0.2674          | 0.8864   |
| 0.161         | 43.0  | 86   | 0.2586          | 0.8864   |
| 0.161         | 44.0  | 88   | 0.4520          | 0.8409   |
| 0.1588        | 45.0  | 90   | 0.4300          | 0.8409   |
| 0.1588        | 46.0  | 92   | 0.2424          | 0.9318   |
| 0.1588        | 47.0  | 94   | 0.2645          | 0.9318   |
| 0.1588        | 48.0  | 96   | 0.2531          | 0.8864   |
| 0.1588        | 49.0  | 98   | 0.2614          | 0.8864   |
| 0.1103        | 50.0  | 100  | 0.3024          | 0.8864   |
| 0.1103        | 51.0  | 102  | 0.2797          | 0.9091   |
| 0.1103        | 52.0  | 104  | 0.2307          | 0.9545   |
| 0.1103        | 53.0  | 106  | 0.2635          | 0.9091   |
| 0.1103        | 54.0  | 108  | 0.5111          | 0.8409   |
| 0.1201        | 55.0  | 110  | 0.5371          | 0.8409   |
| 0.1201        | 56.0  | 112  | 0.2940          | 0.8864   |
| 0.1201        | 57.0  | 114  | 0.3015          | 0.9091   |
| 0.1201        | 58.0  | 116  | 0.2631          | 0.8864   |
| 0.1201        | 59.0  | 118  | 0.2830          | 0.8864   |
| 0.1037        | 60.0  | 120  | 0.3202          | 0.8636   |
| 0.1037        | 61.0  | 122  | 0.3526          | 0.8636   |
| 0.1037        | 62.0  | 124  | 0.3975          | 0.8409   |
| 0.1037        | 63.0  | 126  | 0.4785          | 0.8409   |
| 0.1037        | 64.0  | 128  | 0.4306          | 0.8636   |
| 0.1           | 65.0  | 130  | 0.3230          | 0.8636   |
| 0.1           | 66.0  | 132  | 0.3007          | 0.8864   |
| 0.1           | 67.0  | 134  | 0.2669          | 0.8864   |
| 0.1           | 68.0  | 136  | 0.2335          | 0.8864   |
| 0.1           | 69.0  | 138  | 0.1845          | 0.8864   |
| 0.0984        | 70.0  | 140  | 0.2261          | 0.8864   |
| 0.0984        | 71.0  | 142  | 0.3015          | 0.8864   |
| 0.0984        | 72.0  | 144  | 0.3138          | 0.8864   |
| 0.0984        | 73.0  | 146  | 0.2444          | 0.8864   |
| 0.0984        | 74.0  | 148  | 0.2060          | 0.9091   |
| 0.0826        | 75.0  | 150  | 0.2024          | 0.9318   |
| 0.0826        | 76.0  | 152  | 0.2503          | 0.8864   |
| 0.0826        | 77.0  | 154  | 0.2499          | 0.8864   |
| 0.0826        | 78.0  | 156  | 0.2099          | 0.9091   |
| 0.0826        | 79.0  | 158  | 0.2240          | 0.9091   |
| 0.0701        | 80.0  | 160  | 0.2228          | 0.9091   |
| 0.0701        | 81.0  | 162  | 0.2337          | 0.9091   |
| 0.0701        | 82.0  | 164  | 0.2113          | 0.9318   |
| 0.0701        | 83.0  | 166  | 0.1977          | 0.9091   |
| 0.0701        | 84.0  | 168  | 0.2021          | 0.9091   |
| 0.0846        | 85.0  | 170  | 0.2330          | 0.9318   |
| 0.0846        | 86.0  | 172  | 0.2333          | 0.9318   |
| 0.0846        | 87.0  | 174  | 0.2130          | 0.9318   |
| 0.0846        | 88.0  | 176  | 0.2090          | 0.9091   |
| 0.0846        | 89.0  | 178  | 0.2114          | 0.9091   |
| 0.0932        | 90.0  | 180  | 0.2061          | 0.9091   |
| 0.0932        | 91.0  | 182  | 0.2174          | 0.9091   |
| 0.0932        | 92.0  | 184  | 0.2429          | 0.9091   |
| 0.0932        | 93.0  | 186  | 0.2459          | 0.9091   |
| 0.0932        | 94.0  | 188  | 0.2293          | 0.9318   |
| 0.0742        | 95.0  | 190  | 0.2127          | 0.9318   |
| 0.0742        | 96.0  | 192  | 0.2014          | 0.9091   |
| 0.0742        | 97.0  | 194  | 0.2015          | 0.9091   |
| 0.0742        | 98.0  | 196  | 0.2063          | 0.9318   |
| 0.0742        | 99.0  | 198  | 0.2088          | 0.9318   |
| 0.0701        | 100.0 | 200  | 0.2096          | 0.9318   |


### Framework versions

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

hasta normal