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# beit-base-patch16-224-ve-U13-b-80

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: 0.6397
- Accuracy: 0.8478

## 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: 4e-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: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.3187          | 0.4565   |
| 1.6193        | 2.0   | 13   | 1.3087          | 0.4565   |
| 1.6193        | 2.92  | 19   | 1.2939          | 0.4565   |
| 1.6044        | 4.0   | 26   | 1.2802          | 0.4565   |
| 1.5061        | 4.92  | 32   | 1.2867          | 0.4565   |
| 1.5061        | 6.0   | 39   | 1.2813          | 0.4565   |
| 1.3879        | 6.92  | 45   | 1.2511          | 0.4565   |
| 1.3007        | 8.0   | 52   | 1.1294          | 0.5652   |
| 1.3007        | 8.92  | 58   | 1.0096          | 0.5435   |
| 1.1213        | 10.0  | 65   | 0.9308          | 0.5217   |
| 0.9968        | 10.92 | 71   | 0.9280          | 0.5435   |
| 0.9968        | 12.0  | 78   | 0.8034          | 0.6087   |
| 0.8771        | 12.92 | 84   | 0.7791          | 0.6522   |
| 0.7383        | 14.0  | 91   | 0.8005          | 0.6739   |
| 0.7383        | 14.92 | 97   | 0.7408          | 0.7391   |
| 0.6658        | 16.0  | 104  | 0.9305          | 0.6304   |
| 0.5879        | 16.92 | 110  | 0.7136          | 0.7609   |
| 0.5879        | 18.0  | 117  | 0.7106          | 0.7609   |
| 0.4609        | 18.92 | 123  | 0.6998          | 0.6957   |
| 0.4123        | 20.0  | 130  | 0.7931          | 0.7609   |
| 0.4123        | 20.92 | 136  | 0.9417          | 0.6739   |
| 0.3552        | 22.0  | 143  | 0.7868          | 0.7174   |
| 0.3552        | 22.92 | 149  | 0.9073          | 0.6957   |
| 0.2896        | 24.0  | 156  | 0.8542          | 0.7174   |
| 0.2316        | 24.92 | 162  | 0.7159          | 0.7391   |
| 0.2316        | 26.0  | 169  | 0.7219          | 0.7174   |
| 0.2339        | 26.92 | 175  | 0.7071          | 0.7609   |
| 0.2055        | 28.0  | 182  | 1.0110          | 0.6739   |
| 0.2055        | 28.92 | 188  | 0.6397          | 0.8478   |
| 0.1995        | 30.0  | 195  | 0.6922          | 0.8478   |
| 0.169         | 30.92 | 201  | 0.6171          | 0.8478   |
| 0.169         | 32.0  | 208  | 0.6632          | 0.8261   |
| 0.1586        | 32.92 | 214  | 0.6475          | 0.8261   |
| 0.1439        | 34.0  | 221  | 0.8332          | 0.6957   |
| 0.1439        | 34.92 | 227  | 0.6816          | 0.7826   |
| 0.1698        | 36.0  | 234  | 0.8066          | 0.7609   |
| 0.1362        | 36.92 | 240  | 0.7150          | 0.8043   |
| 0.1362        | 38.0  | 247  | 0.7193          | 0.8043   |
| 0.1344        | 38.92 | 253  | 0.8181          | 0.7609   |
| 0.1317        | 40.0  | 260  | 0.6547          | 0.8261   |
| 0.1317        | 40.92 | 266  | 0.8459          | 0.7609   |
| 0.123         | 42.0  | 273  | 0.7700          | 0.8261   |
| 0.123         | 42.92 | 279  | 0.9338          | 0.7391   |
| 0.102         | 44.0  | 286  | 0.8536          | 0.8043   |
| 0.1015        | 44.92 | 292  | 0.9725          | 0.7391   |
| 0.1015        | 46.0  | 299  | 0.8865          | 0.8043   |
| 0.1313        | 46.92 | 305  | 0.8947          | 0.8261   |
| 0.1312        | 48.0  | 312  | 0.8235          | 0.8043   |
| 0.1312        | 48.92 | 318  | 0.7326          | 0.8261   |
| 0.1168        | 50.0  | 325  | 0.8654          | 0.7609   |
| 0.09          | 50.92 | 331  | 0.7645          | 0.8261   |
| 0.09          | 52.0  | 338  | 0.7632          | 0.8478   |
| 0.0872        | 52.92 | 344  | 0.7496          | 0.8043   |
| 0.0813        | 54.0  | 351  | 0.8846          | 0.8043   |
| 0.0813        | 54.92 | 357  | 0.9214          | 0.7826   |
| 0.0955        | 56.0  | 364  | 0.9284          | 0.7826   |
| 0.1031        | 56.92 | 370  | 0.8855          | 0.7826   |
| 0.1031        | 58.0  | 377  | 0.8619          | 0.8043   |
| 0.0962        | 58.92 | 383  | 0.8187          | 0.8261   |
| 0.0891        | 60.0  | 390  | 0.7430          | 0.8478   |
| 0.0891        | 60.92 | 396  | 0.7530          | 0.8478   |
| 0.0679        | 62.0  | 403  | 0.7790          | 0.8261   |
| 0.0679        | 62.92 | 409  | 0.7905          | 0.8261   |
| 0.0805        | 64.0  | 416  | 0.8286          | 0.8261   |
| 0.0619        | 64.92 | 422  | 0.8371          | 0.8043   |
| 0.0619        | 66.0  | 429  | 0.8655          | 0.8043   |
| 0.0778        | 66.92 | 435  | 0.8897          | 0.8043   |
| 0.0712        | 68.0  | 442  | 0.9385          | 0.8043   |
| 0.0712        | 68.92 | 448  | 0.9611          | 0.8043   |
| 0.0659        | 70.0  | 455  | 0.9597          | 0.8043   |
| 0.0602        | 70.92 | 461  | 0.9635          | 0.8043   |
| 0.0602        | 72.0  | 468  | 0.9733          | 0.8043   |
| 0.0641        | 72.92 | 474  | 0.9754          | 0.8043   |
| 0.0653        | 73.85 | 480  | 0.9753          | 0.8043   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0

avanzada leve moderada no dmae