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# beit-base-patch16-224-fold4

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: 0.8625
- 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    | 0.8664          | 0.3797   |
| No log        | 2.0     | 7    | 0.8144          | 0.4810   |
| 0.7345        | 2.8571  | 10   | 0.6451          | 0.5823   |
| 0.7345        | 4.0     | 14   | 0.7268          | 0.5190   |
| 0.7345        | 4.8571  | 17   | 0.5731          | 0.7342   |
| 0.6447        | 6.0     | 21   | 0.6948          | 0.5316   |
| 0.6447        | 6.8571  | 24   | 0.5315          | 0.6962   |
| 0.6447        | 8.0     | 28   | 0.5292          | 0.6835   |
| 0.5582        | 8.8571  | 31   | 0.6226          | 0.5823   |
| 0.5582        | 10.0    | 35   | 0.5479          | 0.6329   |
| 0.5582        | 10.8571 | 38   | 0.5230          | 0.7975   |
| 0.4807        | 12.0    | 42   | 0.6146          | 0.6709   |
| 0.4807        | 12.8571 | 45   | 0.6346          | 0.6709   |
| 0.4807        | 14.0    | 49   | 1.0584          | 0.5823   |
| 0.4441        | 14.8571 | 52   | 0.4716          | 0.7848   |
| 0.4441        | 16.0    | 56   | 0.4454          | 0.7595   |
| 0.4441        | 16.8571 | 59   | 0.5688          | 0.7595   |
| 0.3829        | 18.0    | 63   | 0.5233          | 0.7975   |
| 0.3829        | 18.8571 | 66   | 0.5291          | 0.7975   |
| 0.3352        | 20.0    | 70   | 0.4981          | 0.7848   |
| 0.3352        | 20.8571 | 73   | 0.8590          | 0.7468   |
| 0.3352        | 22.0    | 77   | 0.5201          | 0.7975   |
| 0.341         | 22.8571 | 80   | 0.6530          | 0.7468   |
| 0.341         | 24.0    | 84   | 0.5732          | 0.7848   |
| 0.341         | 24.8571 | 87   | 0.6532          | 0.7975   |
| 0.2554        | 26.0    | 91   | 0.5656          | 0.7722   |
| 0.2554        | 26.8571 | 94   | 0.8085          | 0.7595   |
| 0.2554        | 28.0    | 98   | 0.4826          | 0.7848   |
| 0.325         | 28.8571 | 101  | 0.8227          | 0.7468   |
| 0.325         | 30.0    | 105  | 0.5349          | 0.7975   |
| 0.325         | 30.8571 | 108  | 0.7056          | 0.7722   |
| 0.2572        | 32.0    | 112  | 0.5415          | 0.7848   |
| 0.2572        | 32.8571 | 115  | 0.5953          | 0.7848   |
| 0.2572        | 34.0    | 119  | 0.5884          | 0.7848   |
| 0.1994        | 34.8571 | 122  | 0.5971          | 0.7975   |
| 0.1994        | 36.0    | 126  | 0.8481          | 0.7468   |
| 0.1994        | 36.8571 | 129  | 0.6107          | 0.7595   |
| 0.209         | 38.0    | 133  | 0.9242          | 0.7848   |
| 0.209         | 38.8571 | 136  | 0.7106          | 0.7722   |
| 0.188         | 40.0    | 140  | 0.9581          | 0.7722   |
| 0.188         | 40.8571 | 143  | 0.9282          | 0.7722   |
| 0.188         | 42.0    | 147  | 1.0447          | 0.7848   |
| 0.1982        | 42.8571 | 150  | 0.9748          | 0.7722   |
| 0.1982        | 44.0    | 154  | 0.7132          | 0.7848   |
| 0.1982        | 44.8571 | 157  | 0.6957          | 0.7848   |
| 0.1799        | 46.0    | 161  | 0.8674          | 0.7848   |
| 0.1799        | 46.8571 | 164  | 0.9036          | 0.7848   |
| 0.1799        | 48.0    | 168  | 0.9910          | 0.7848   |
| 0.1502        | 48.8571 | 171  | 1.0821          | 0.7722   |
| 0.1502        | 50.0    | 175  | 0.8117          | 0.7848   |
| 0.1502        | 50.8571 | 178  | 0.9037          | 0.7722   |
| 0.1591        | 52.0    | 182  | 0.8272          | 0.7722   |
| 0.1591        | 52.8571 | 185  | 1.0109          | 0.7848   |
| 0.1591        | 54.0    | 189  | 0.8490          | 0.7722   |
| 0.1588        | 54.8571 | 192  | 0.8973          | 0.7722   |
| 0.1588        | 56.0    | 196  | 0.9084          | 0.7722   |
| 0.1588        | 56.8571 | 199  | 0.8034          | 0.7595   |
| 0.1353        | 58.0    | 203  | 0.8885          | 0.7848   |
| 0.1353        | 58.8571 | 206  | 1.0837          | 0.7848   |
| 0.1308        | 60.0    | 210  | 0.8627          | 0.7975   |
| 0.1308        | 60.8571 | 213  | 0.9842          | 0.8101   |
| 0.1308        | 62.0    | 217  | 0.9966          | 0.7975   |
| 0.1402        | 62.8571 | 220  | 0.9639          | 0.7848   |
| 0.1402        | 64.0    | 224  | 1.0104          | 0.7848   |
| 0.1402        | 64.8571 | 227  | 0.8940          | 0.7722   |
| 0.1301        | 66.0    | 231  | 0.9349          | 0.7848   |
| 0.1301        | 66.8571 | 234  | 1.1485          | 0.7848   |
| 0.1301        | 68.0    | 238  | 1.0021          | 0.7848   |
| 0.1399        | 68.8571 | 241  | 0.8971          | 0.7975   |
| 0.1399        | 70.0    | 245  | 0.8604          | 0.7975   |
| 0.1399        | 70.8571 | 248  | 0.8625          | 0.8228   |
| 0.1203        | 72.0    | 252  | 1.0301          | 0.7975   |
| 0.1203        | 72.8571 | 255  | 1.2355          | 0.7722   |
| 0.1203        | 74.0    | 259  | 1.0716          | 0.7848   |
| 0.1385        | 74.8571 | 262  | 0.9598          | 0.7975   |
| 0.1385        | 76.0    | 266  | 0.9965          | 0.7975   |
| 0.1385        | 76.8571 | 269  | 1.1018          | 0.7975   |
| 0.115         | 78.0    | 273  | 1.0895          | 0.7975   |
| 0.115         | 78.8571 | 276  | 1.0261          | 0.7848   |
| 0.1227        | 80.0    | 280  | 0.9800          | 0.7975   |
| 0.1227        | 80.8571 | 283  | 0.9960          | 0.7848   |
| 0.1227        | 82.0    | 287  | 1.0251          | 0.7848   |
| 0.1044        | 82.8571 | 290  | 1.0236          | 0.7848   |
| 0.1044        | 84.0    | 294  | 1.0139          | 0.7848   |
| 0.1044        | 84.8571 | 297  | 1.0073          | 0.7848   |
| 0.1246        | 85.7143 | 300  | 1.0066          | 0.7848   |


### Framework versions

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

hasta normal