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# beit-base-patch16-224-fold1

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: 0.7241
- Accuracy: 0.8481

## 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    | 0.8050          | 0.4557   |
| No log        | 2.0     | 7    | 0.7151          | 0.5696   |
| 0.8103        | 2.8571  | 10   | 0.6822          | 0.5570   |
| 0.8103        | 4.0     | 14   | 0.6408          | 0.5696   |
| 0.8103        | 4.8571  | 17   | 0.6244          | 0.6709   |
| 0.6583        | 6.0     | 21   | 0.5893          | 0.6709   |
| 0.6583        | 6.8571  | 24   | 0.5877          | 0.6329   |
| 0.6583        | 8.0     | 28   | 0.5752          | 0.6835   |
| 0.5912        | 8.8571  | 31   | 0.5826          | 0.6456   |
| 0.5912        | 10.0    | 35   | 0.5469          | 0.6835   |
| 0.5912        | 10.8571 | 38   | 0.6173          | 0.6582   |
| 0.5301        | 12.0    | 42   | 0.5151          | 0.6962   |
| 0.5301        | 12.8571 | 45   | 0.5105          | 0.6962   |
| 0.5301        | 14.0    | 49   | 0.5489          | 0.7089   |
| 0.4703        | 14.8571 | 52   | 0.5725          | 0.6835   |
| 0.4703        | 16.0    | 56   | 0.5560          | 0.6962   |
| 0.4703        | 16.8571 | 59   | 0.5824          | 0.6709   |
| 0.4189        | 18.0    | 63   | 0.5401          | 0.7468   |
| 0.4189        | 18.8571 | 66   | 0.5147          | 0.7722   |
| 0.3741        | 20.0    | 70   | 0.4864          | 0.7595   |
| 0.3741        | 20.8571 | 73   | 0.5272          | 0.7342   |
| 0.3741        | 22.0    | 77   | 0.4914          | 0.7468   |
| 0.387         | 22.8571 | 80   | 0.5658          | 0.7468   |
| 0.387         | 24.0    | 84   | 0.4662          | 0.7722   |
| 0.387         | 24.8571 | 87   | 0.4376          | 0.7848   |
| 0.3502        | 26.0    | 91   | 0.5367          | 0.7722   |
| 0.3502        | 26.8571 | 94   | 0.5490          | 0.7342   |
| 0.3502        | 28.0    | 98   | 0.7163          | 0.7722   |
| 0.3148        | 28.8571 | 101  | 0.6005          | 0.7468   |
| 0.3148        | 30.0    | 105  | 0.6501          | 0.7722   |
| 0.3148        | 30.8571 | 108  | 0.5313          | 0.7975   |
| 0.2973        | 32.0    | 112  | 0.5466          | 0.7722   |
| 0.2973        | 32.8571 | 115  | 0.5731          | 0.8101   |
| 0.2973        | 34.0    | 119  | 0.6544          | 0.8101   |
| 0.2474        | 34.8571 | 122  | 0.6061          | 0.7848   |
| 0.2474        | 36.0    | 126  | 0.5816          | 0.7722   |
| 0.2474        | 36.8571 | 129  | 0.7161          | 0.7595   |
| 0.2033        | 38.0    | 133  | 0.6235          | 0.7848   |
| 0.2033        | 38.8571 | 136  | 0.7889          | 0.7595   |
| 0.2338        | 40.0    | 140  | 0.5943          | 0.7595   |
| 0.2338        | 40.8571 | 143  | 0.6170          | 0.7342   |
| 0.2338        | 42.0    | 147  | 0.6964          | 0.6962   |
| 0.2067        | 42.8571 | 150  | 0.7154          | 0.7468   |
| 0.2067        | 44.0    | 154  | 0.7675          | 0.7722   |
| 0.2067        | 44.8571 | 157  | 0.7766          | 0.7468   |
| 0.2133        | 46.0    | 161  | 0.9330          | 0.7848   |
| 0.2133        | 46.8571 | 164  | 0.6494          | 0.7975   |
| 0.2133        | 48.0    | 168  | 0.5709          | 0.7722   |
| 0.2004        | 48.8571 | 171  | 0.6462          | 0.8101   |
| 0.2004        | 50.0    | 175  | 0.6668          | 0.7722   |
| 0.2004        | 50.8571 | 178  | 0.6305          | 0.8101   |
| 0.188         | 52.0    | 182  | 0.7189          | 0.8228   |
| 0.188         | 52.8571 | 185  | 0.6853          | 0.7848   |
| 0.188         | 54.0    | 189  | 0.8040          | 0.8228   |
| 0.1623        | 54.8571 | 192  | 0.6958          | 0.8101   |
| 0.1623        | 56.0    | 196  | 0.6907          | 0.8101   |
| 0.1623        | 56.8571 | 199  | 0.6821          | 0.8101   |
| 0.1588        | 58.0    | 203  | 0.6534          | 0.8101   |
| 0.1588        | 58.8571 | 206  | 0.7192          | 0.8101   |
| 0.1607        | 60.0    | 210  | 0.7753          | 0.8228   |
| 0.1607        | 60.8571 | 213  | 0.8950          | 0.8101   |
| 0.1607        | 62.0    | 217  | 0.7904          | 0.8101   |
| 0.1767        | 62.8571 | 220  | 0.6973          | 0.8101   |
| 0.1767        | 64.0    | 224  | 0.6694          | 0.7975   |
| 0.1767        | 64.8571 | 227  | 0.6339          | 0.8101   |
| 0.1463        | 66.0    | 231  | 0.6530          | 0.8101   |
| 0.1463        | 66.8571 | 234  | 0.6142          | 0.8101   |
| 0.1463        | 68.0    | 238  | 0.6290          | 0.8228   |
| 0.1287        | 68.8571 | 241  | 0.6334          | 0.8354   |
| 0.1287        | 70.0    | 245  | 0.8059          | 0.8101   |
| 0.1287        | 70.8571 | 248  | 0.7241          | 0.8481   |
| 0.1323        | 72.0    | 252  | 0.6836          | 0.8481   |
| 0.1323        | 72.8571 | 255  | 0.6588          | 0.8228   |
| 0.1323        | 74.0    | 259  | 0.6598          | 0.8481   |
| 0.1042        | 74.8571 | 262  | 0.7139          | 0.8354   |
| 0.1042        | 76.0    | 266  | 0.7236          | 0.8354   |
| 0.1042        | 76.8571 | 269  | 0.6919          | 0.8354   |
| 0.1106        | 78.0    | 273  | 0.6568          | 0.8354   |
| 0.1106        | 78.8571 | 276  | 0.6556          | 0.8481   |
| 0.1348        | 80.0    | 280  | 0.6612          | 0.8354   |
| 0.1348        | 80.8571 | 283  | 0.6686          | 0.8228   |
| 0.1348        | 82.0    | 287  | 0.6705          | 0.8481   |
| 0.1352        | 82.8571 | 290  | 0.6776          | 0.8354   |
| 0.1352        | 84.0    | 294  | 0.6873          | 0.8354   |
| 0.1352        | 84.8571 | 297  | 0.6888          | 0.8354   |
| 0.1226        | 85.7143 | 300  | 0.6880          | 0.8354   |


### Framework versions

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

hasta normal