
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# beit-base-patch16-224-fold5

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: 0.6919
- Accuracy: 0.8228

## 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    | 0.6964          | 0.4937   |
| No log        | 2.0     | 7    | 0.6336          | 0.6456   |
| 0.7161        | 2.8571  | 10   | 0.6712          | 0.5063   |
| 0.7161        | 4.0     | 14   | 0.5884          | 0.6835   |
| 0.7161        | 4.8571  | 17   | 0.6325          | 0.5570   |
| 0.6466        | 6.0     | 21   | 0.6307          | 0.6076   |
| 0.6466        | 6.8571  | 24   | 0.5518          | 0.6835   |
| 0.6466        | 8.0     | 28   | 0.6856          | 0.6456   |
| 0.5604        | 8.8571  | 31   | 0.5678          | 0.7089   |
| 0.5604        | 10.0    | 35   | 0.5764          | 0.6329   |
| 0.5604        | 10.8571 | 38   | 0.6124          | 0.6456   |
| 0.4941        | 12.0    | 42   | 1.1315          | 0.5316   |
| 0.4941        | 12.8571 | 45   | 0.5624          | 0.6835   |
| 0.4941        | 14.0    | 49   | 0.6351          | 0.6962   |
| 0.4516        | 14.8571 | 52   | 0.6811          | 0.6835   |
| 0.4516        | 16.0    | 56   | 0.7385          | 0.6456   |
| 0.4516        | 16.8571 | 59   | 0.6123          | 0.7215   |
| 0.409         | 18.0    | 63   | 0.5877          | 0.6835   |
| 0.409         | 18.8571 | 66   | 0.6250          | 0.6962   |
| 0.3439        | 20.0    | 70   | 0.6220          | 0.7342   |
| 0.3439        | 20.8571 | 73   | 0.7250          | 0.7089   |
| 0.3439        | 22.0    | 77   | 0.6107          | 0.7342   |
| 0.3268        | 22.8571 | 80   | 0.4999          | 0.7975   |
| 0.3268        | 24.0    | 84   | 0.5325          | 0.7468   |
| 0.3268        | 24.8571 | 87   | 0.7209          | 0.7342   |
| 0.2941        | 26.0    | 91   | 0.5557          | 0.7722   |
| 0.2941        | 26.8571 | 94   | 0.6655          | 0.7595   |
| 0.2941        | 28.0    | 98   | 1.0775          | 0.6962   |
| 0.284         | 28.8571 | 101  | 0.6817          | 0.7595   |
| 0.284         | 30.0    | 105  | 0.9235          | 0.6835   |
| 0.284         | 30.8571 | 108  | 0.6587          | 0.7595   |
| 0.3134        | 32.0    | 112  | 0.7086          | 0.7468   |
| 0.3134        | 32.8571 | 115  | 0.6895          | 0.7468   |
| 0.3134        | 34.0    | 119  | 0.6418          | 0.7722   |
| 0.2266        | 34.8571 | 122  | 0.7007          | 0.7848   |
| 0.2266        | 36.0    | 126  | 0.6919          | 0.8228   |
| 0.2266        | 36.8571 | 129  | 0.7562          | 0.7342   |
| 0.2249        | 38.0    | 133  | 0.6775          | 0.7722   |
| 0.2249        | 38.8571 | 136  | 0.7787          | 0.7595   |
| 0.2181        | 40.0    | 140  | 0.7932          | 0.7722   |
| 0.2181        | 40.8571 | 143  | 0.9334          | 0.7595   |
| 0.2181        | 42.0    | 147  | 0.8224          | 0.7468   |
| 0.186         | 42.8571 | 150  | 0.8444          | 0.7722   |
| 0.186         | 44.0    | 154  | 1.0350          | 0.7722   |
| 0.186         | 44.8571 | 157  | 0.8386          | 0.7722   |
| 0.1882        | 46.0    | 161  | 0.8384          | 0.7722   |
| 0.1882        | 46.8571 | 164  | 0.7905          | 0.7595   |
| 0.1882        | 48.0    | 168  | 0.7184          | 0.7722   |
| 0.1649        | 48.8571 | 171  | 0.8119          | 0.7595   |
| 0.1649        | 50.0    | 175  | 0.7172          | 0.7722   |
| 0.1649        | 50.8571 | 178  | 0.9249          | 0.7722   |
| 0.1847        | 52.0    | 182  | 0.8069          | 0.7722   |
| 0.1847        | 52.8571 | 185  | 0.8753          | 0.7722   |
| 0.1847        | 54.0    | 189  | 0.8822          | 0.7722   |
| 0.1606        | 54.8571 | 192  | 0.7481          | 0.7975   |
| 0.1606        | 56.0    | 196  | 0.7300          | 0.7722   |
| 0.1606        | 56.8571 | 199  | 0.7325          | 0.8101   |
| 0.142         | 58.0    | 203  | 0.7088          | 0.8228   |
| 0.142         | 58.8571 | 206  | 0.6900          | 0.8228   |
| 0.1546        | 60.0    | 210  | 0.8303          | 0.7722   |
| 0.1546        | 60.8571 | 213  | 0.8218          | 0.7975   |
| 0.1546        | 62.0    | 217  | 0.9628          | 0.7848   |
| 0.1608        | 62.8571 | 220  | 0.9826          | 0.7848   |
| 0.1608        | 64.0    | 224  | 0.7604          | 0.7595   |
| 0.1608        | 64.8571 | 227  | 0.8165          | 0.7722   |
| 0.1418        | 66.0    | 231  | 0.8280          | 0.7722   |
| 0.1418        | 66.8571 | 234  | 0.9254          | 0.7848   |
| 0.1418        | 68.0    | 238  | 0.8439          | 0.7848   |
| 0.1505        | 68.8571 | 241  | 0.8096          | 0.7975   |
| 0.1505        | 70.0    | 245  | 0.9471          | 0.7595   |
| 0.1505        | 70.8571 | 248  | 0.9028          | 0.7595   |
| 0.1211        | 72.0    | 252  | 0.7744          | 0.7975   |
| 0.1211        | 72.8571 | 255  | 0.7756          | 0.8101   |
| 0.1211        | 74.0    | 259  | 0.7904          | 0.8101   |
| 0.1248        | 74.8571 | 262  | 0.8036          | 0.8101   |
| 0.1248        | 76.0    | 266  | 0.8592          | 0.7848   |
| 0.1248        | 76.8571 | 269  | 0.8946          | 0.7848   |
| 0.122         | 78.0    | 273  | 0.8576          | 0.7848   |
| 0.122         | 78.8571 | 276  | 0.9037          | 0.7975   |
| 0.1129        | 80.0    | 280  | 0.9982          | 0.7848   |
| 0.1129        | 80.8571 | 283  | 1.0404          | 0.7722   |
| 0.1129        | 82.0    | 287  | 0.9969          | 0.7975   |
| 0.1136        | 82.8571 | 290  | 0.9586          | 0.7975   |
| 0.1136        | 84.0    | 294  | 0.9200          | 0.7848   |
| 0.1136        | 84.8571 | 297  | 0.9063          | 0.7722   |
| 0.1233        | 85.7143 | 300  | 0.9050          | 0.7722   |


### Framework versions

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

hasta normal