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# deit-base-distilled-patch16-224-55-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: 0.5842
- Accuracy: 0.8101

## 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        | 0.8571  | 3    | 0.7763          | 0.5443   |
| No log        | 2.0     | 7    | 0.6780          | 0.6203   |
| 0.721         | 2.8571  | 10   | 0.6954          | 0.5316   |
| 0.721         | 4.0     | 14   | 0.6370          | 0.6203   |
| 0.721         | 4.8571  | 17   | 0.6105          | 0.5949   |
| 0.6207        | 6.0     | 21   | 0.5798          | 0.6835   |
| 0.6207        | 6.8571  | 24   | 0.5704          | 0.7468   |
| 0.6207        | 8.0     | 28   | 0.5879          | 0.7089   |
| 0.5427        | 8.8571  | 31   | 0.6727          | 0.6582   |
| 0.5427        | 10.0    | 35   | 0.5841          | 0.6962   |
| 0.5427        | 10.8571 | 38   | 0.6059          | 0.6962   |
| 0.4775        | 12.0    | 42   | 1.0271          | 0.6076   |
| 0.4775        | 12.8571 | 45   | 0.6412          | 0.7089   |
| 0.4775        | 14.0    | 49   | 0.8064          | 0.6582   |
| 0.4961        | 14.8571 | 52   | 0.5600          | 0.6582   |
| 0.4961        | 16.0    | 56   | 0.5889          | 0.6709   |
| 0.4961        | 16.8571 | 59   | 0.8381          | 0.6835   |
| 0.4391        | 18.0    | 63   | 0.6725          | 0.6962   |
| 0.4391        | 18.8571 | 66   | 0.5350          | 0.7215   |
| 0.413         | 20.0    | 70   | 0.6033          | 0.7089   |
| 0.413         | 20.8571 | 73   | 0.7280          | 0.6835   |
| 0.413         | 22.0    | 77   | 0.6082          | 0.7342   |
| 0.336         | 22.8571 | 80   | 0.6530          | 0.7595   |
| 0.336         | 24.0    | 84   | 0.6922          | 0.7089   |
| 0.336         | 24.8571 | 87   | 0.6649          | 0.7089   |
| 0.2745        | 26.0    | 91   | 0.7311          | 0.7089   |
| 0.2745        | 26.8571 | 94   | 0.7192          | 0.7089   |
| 0.2745        | 28.0    | 98   | 0.7408          | 0.7215   |
| 0.2494        | 28.8571 | 101  | 0.5842          | 0.8101   |
| 0.2494        | 30.0    | 105  | 0.5949          | 0.7595   |
| 0.2494        | 30.8571 | 108  | 0.6885          | 0.7468   |
| 0.2291        | 32.0    | 112  | 0.8746          | 0.7089   |
| 0.2291        | 32.8571 | 115  | 0.8005          | 0.7089   |
| 0.2291        | 34.0    | 119  | 0.7034          | 0.7342   |
| 0.2           | 34.8571 | 122  | 0.7047          | 0.7089   |
| 0.2           | 36.0    | 126  | 0.8362          | 0.7342   |
| 0.2           | 36.8571 | 129  | 0.8509          | 0.7468   |
| 0.1674        | 38.0    | 133  | 0.9237          | 0.7595   |
| 0.1674        | 38.8571 | 136  | 0.7527          | 0.7595   |
| 0.1764        | 40.0    | 140  | 0.7904          | 0.7468   |
| 0.1764        | 40.8571 | 143  | 0.7333          | 0.7595   |
| 0.1764        | 42.0    | 147  | 0.7778          | 0.7342   |
| 0.1706        | 42.8571 | 150  | 0.7342          | 0.7722   |
| 0.1706        | 44.0    | 154  | 0.8144          | 0.7468   |
| 0.1706        | 44.8571 | 157  | 0.8299          | 0.7595   |
| 0.1617        | 46.0    | 161  | 1.0111          | 0.7468   |
| 0.1617        | 46.8571 | 164  | 0.8602          | 0.7595   |
| 0.1617        | 48.0    | 168  | 0.8332          | 0.7342   |
| 0.1622        | 48.8571 | 171  | 0.8297          | 0.7468   |
| 0.1622        | 50.0    | 175  | 0.8817          | 0.7595   |
| 0.1622        | 50.8571 | 178  | 0.8742          | 0.7595   |
| 0.1437        | 52.0    | 182  | 1.0696          | 0.7595   |
| 0.1437        | 52.8571 | 185  | 0.9412          | 0.7595   |
| 0.1437        | 54.0    | 189  | 0.7411          | 0.7975   |
| 0.1492        | 54.8571 | 192  | 0.9043          | 0.7595   |
| 0.1492        | 56.0    | 196  | 0.7936          | 0.7848   |
| 0.1492        | 56.8571 | 199  | 0.8231          | 0.7722   |
| 0.1279        | 58.0    | 203  | 1.0894          | 0.7722   |
| 0.1279        | 58.8571 | 206  | 1.0071          | 0.7975   |
| 0.1317        | 60.0    | 210  | 0.9893          | 0.7722   |
| 0.1317        | 60.8571 | 213  | 1.0476          | 0.7468   |
| 0.1317        | 62.0    | 217  | 0.8081          | 0.7848   |
| 0.1456        | 62.8571 | 220  | 0.8136          | 0.7468   |
| 0.1456        | 64.0    | 224  | 0.9613          | 0.7848   |
| 0.1456        | 64.8571 | 227  | 0.9783          | 0.7848   |
| 0.119         | 66.0    | 231  | 1.0226          | 0.7722   |
| 0.119         | 66.8571 | 234  | 1.0810          | 0.7722   |
| 0.119         | 68.0    | 238  | 0.9606          | 0.7975   |
| 0.1323        | 68.8571 | 241  | 0.9852          | 0.7848   |
| 0.1323        | 70.0    | 245  | 0.8826          | 0.7595   |
| 0.1323        | 70.8571 | 248  | 0.8169          | 0.7468   |
| 0.126         | 72.0    | 252  | 0.8815          | 0.7595   |
| 0.126         | 72.8571 | 255  | 0.9871          | 0.7722   |
| 0.126         | 74.0    | 259  | 0.8927          | 0.7722   |
| 0.1013        | 74.8571 | 262  | 0.8365          | 0.7468   |
| 0.1013        | 76.0    | 266  | 0.8423          | 0.7468   |
| 0.1013        | 76.8571 | 269  | 0.8331          | 0.7468   |
| 0.1142        | 78.0    | 273  | 0.8204          | 0.7722   |
| 0.1142        | 78.8571 | 276  | 0.8286          | 0.7722   |
| 0.1287        | 80.0    | 280  | 0.8702          | 0.7722   |
| 0.1287        | 80.8571 | 283  | 0.9070          | 0.7722   |
| 0.1287        | 82.0    | 287  | 0.9025          | 0.7722   |
| 0.099         | 82.8571 | 290  | 0.8806          | 0.7722   |
| 0.099         | 84.0    | 294  | 0.8637          | 0.7595   |
| 0.099         | 84.8571 | 297  | 0.8578          | 0.7595   |
| 0.1141        | 85.7143 | 300  | 0.8551          | 0.7468   |


### Framework versions

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

hasta normal