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# beit-base-patch16-224-fold2

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3405
- Accuracy: 0.8608

## 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    | 0.6785          | 0.6076   |
| No log        | 2.0     | 7    | 0.6621          | 0.6329   |
| 0.7083        | 2.8571  | 10   | 0.6434          | 0.5823   |
| 0.7083        | 4.0     | 14   | 0.6708          | 0.5696   |
| 0.7083        | 4.8571  | 17   | 0.6701          | 0.6076   |
| 0.6009        | 6.0     | 21   | 0.7958          | 0.5949   |
| 0.6009        | 6.8571  | 24   | 0.5952          | 0.6456   |
| 0.6009        | 8.0     | 28   | 0.8008          | 0.6962   |
| 0.5315        | 8.8571  | 31   | 0.8903          | 0.6329   |
| 0.5315        | 10.0    | 35   | 0.7070          | 0.6709   |
| 0.5315        | 10.8571 | 38   | 0.5331          | 0.7595   |
| 0.5756        | 12.0    | 42   | 0.5307          | 0.7468   |
| 0.5756        | 12.8571 | 45   | 0.5070          | 0.7468   |
| 0.5756        | 14.0    | 49   | 0.6117          | 0.7215   |
| 0.4519        | 14.8571 | 52   | 0.4667          | 0.7468   |
| 0.4519        | 16.0    | 56   | 0.4151          | 0.7848   |
| 0.4519        | 16.8571 | 59   | 0.4435          | 0.7722   |
| 0.3821        | 18.0    | 63   | 0.4114          | 0.7975   |
| 0.3821        | 18.8571 | 66   | 0.4067          | 0.8101   |
| 0.328         | 20.0    | 70   | 0.4459          | 0.8101   |
| 0.328         | 20.8571 | 73   | 0.3859          | 0.8354   |
| 0.328         | 22.0    | 77   | 0.3405          | 0.8608   |
| 0.3344        | 22.8571 | 80   | 0.3702          | 0.8354   |
| 0.3344        | 24.0    | 84   | 0.4352          | 0.7848   |
| 0.3344        | 24.8571 | 87   | 0.6777          | 0.7342   |
| 0.2747        | 26.0    | 91   | 0.5708          | 0.7975   |
| 0.2747        | 26.8571 | 94   | 0.4432          | 0.8101   |
| 0.2747        | 28.0    | 98   | 0.3736          | 0.8101   |
| 0.2634        | 28.8571 | 101  | 0.3938          | 0.8228   |
| 0.2634        | 30.0    | 105  | 0.4460          | 0.8354   |
| 0.2634        | 30.8571 | 108  | 0.4382          | 0.8101   |
| 0.2306        | 32.0    | 112  | 0.5574          | 0.8101   |
| 0.2306        | 32.8571 | 115  | 0.3863          | 0.8354   |
| 0.2306        | 34.0    | 119  | 0.4390          | 0.8481   |
| 0.2214        | 34.8571 | 122  | 0.4839          | 0.8481   |
| 0.2214        | 36.0    | 126  | 0.4523          | 0.8354   |
| 0.2214        | 36.8571 | 129  | 0.4022          | 0.8354   |
| 0.1945        | 38.0    | 133  | 0.4408          | 0.8354   |
| 0.1945        | 38.8571 | 136  | 0.3988          | 0.8354   |
| 0.1863        | 40.0    | 140  | 0.4467          | 0.8481   |
| 0.1863        | 40.8571 | 143  | 0.4788          | 0.8101   |
| 0.1863        | 42.0    | 147  | 0.4749          | 0.8354   |
| 0.1718        | 42.8571 | 150  | 0.4727          | 0.8228   |
| 0.1718        | 44.0    | 154  | 0.4632          | 0.8481   |
| 0.1718        | 44.8571 | 157  | 0.4561          | 0.8354   |
| 0.1535        | 46.0    | 161  | 0.5113          | 0.8101   |
| 0.1535        | 46.8571 | 164  | 0.6505          | 0.8481   |
| 0.1535        | 48.0    | 168  | 0.5612          | 0.8228   |
| 0.1454        | 48.8571 | 171  | 0.6825          | 0.8354   |
| 0.1454        | 50.0    | 175  | 0.7960          | 0.8354   |
| 0.1454        | 50.8571 | 178  | 0.5915          | 0.8228   |
| 0.1327        | 52.0    | 182  | 0.6200          | 0.8354   |
| 0.1327        | 52.8571 | 185  | 0.4977          | 0.8354   |
| 0.1327        | 54.0    | 189  | 0.6180          | 0.8608   |
| 0.1491        | 54.8571 | 192  | 0.6474          | 0.8608   |
| 0.1491        | 56.0    | 196  | 0.5886          | 0.8481   |
| 0.1491        | 56.8571 | 199  | 0.6743          | 0.8481   |
| 0.1666        | 58.0    | 203  | 0.6476          | 0.8354   |
| 0.1666        | 58.8571 | 206  | 0.6483          | 0.8481   |
| 0.1219        | 60.0    | 210  | 0.7216          | 0.8354   |
| 0.1219        | 60.8571 | 213  | 0.6541          | 0.8354   |
| 0.1219        | 62.0    | 217  | 0.6636          | 0.8354   |
| 0.1339        | 62.8571 | 220  | 0.6708          | 0.8354   |
| 0.1339        | 64.0    | 224  | 0.6735          | 0.8481   |
| 0.1339        | 64.8571 | 227  | 0.7030          | 0.8354   |
| 0.1227        | 66.0    | 231  | 0.6779          | 0.8228   |
| 0.1227        | 66.8571 | 234  | 0.7091          | 0.8354   |
| 0.1227        | 68.0    | 238  | 0.6858          | 0.8354   |
| 0.1316        | 68.8571 | 241  | 0.6668          | 0.8354   |
| 0.1316        | 70.0    | 245  | 0.6491          | 0.8354   |
| 0.1316        | 70.8571 | 248  | 0.7164          | 0.8481   |
| 0.1124        | 72.0    | 252  | 0.8063          | 0.8354   |
| 0.1124        | 72.8571 | 255  | 0.7437          | 0.8481   |
| 0.1124        | 74.0    | 259  | 0.8528          | 0.8354   |
| 0.1036        | 74.8571 | 262  | 0.9348          | 0.8101   |
| 0.1036        | 76.0    | 266  | 0.8078          | 0.8354   |
| 0.1036        | 76.8571 | 269  | 0.7697          | 0.8481   |
| 0.1057        | 78.0    | 273  | 0.8040          | 0.8481   |
| 0.1057        | 78.8571 | 276  | 0.8197          | 0.8481   |
| 0.099         | 80.0    | 280  | 0.8256          | 0.8354   |
| 0.099         | 80.8571 | 283  | 0.8057          | 0.8228   |
| 0.099         | 82.0    | 287  | 0.7797          | 0.8354   |
| 0.0927        | 82.8571 | 290  | 0.7807          | 0.8354   |
| 0.0927        | 84.0    | 294  | 0.7957          | 0.8228   |
| 0.0927        | 84.8571 | 297  | 0.8031          | 0.8228   |
| 0.0995        | 85.7143 | 300  | 0.8061          | 0.8228   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

hasta normal