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

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: 0.7122
- 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: 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: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.3182          | 0.4565   |
| 1.6182        | 2.0   | 13   | 1.3056          | 0.4565   |
| 1.6182        | 2.92  | 19   | 1.2884          | 0.4565   |
| 1.592         | 4.0   | 26   | 1.2807          | 0.4565   |
| 1.4756        | 4.92  | 32   | 1.2991          | 0.4565   |
| 1.4756        | 6.0   | 39   | 1.2451          | 0.5      |
| 1.352         | 6.92  | 45   | 1.1845          | 0.5217   |
| 1.2143        | 8.0   | 52   | 1.0315          | 0.6087   |
| 1.2143        | 8.92  | 58   | 0.9289          | 0.5435   |
| 1.0327        | 10.0  | 65   | 0.8925          | 0.5435   |
| 0.8878        | 10.92 | 71   | 0.8633          | 0.5652   |
| 0.8878        | 12.0  | 78   | 0.7566          | 0.6304   |
| 0.7712        | 12.92 | 84   | 0.7669          | 0.7609   |
| 0.6808        | 14.0  | 91   | 0.7635          | 0.7609   |
| 0.6808        | 14.92 | 97   | 0.8653          | 0.6304   |
| 0.5844        | 16.0  | 104  | 0.7193          | 0.7174   |
| 0.4332        | 16.92 | 110  | 0.6186          | 0.7826   |
| 0.4332        | 18.0  | 117  | 1.0295          | 0.6739   |
| 0.3607        | 18.92 | 123  | 0.8007          | 0.7609   |
| 0.3134        | 20.0  | 130  | 0.6790          | 0.7826   |
| 0.3134        | 20.92 | 136  | 0.8013          | 0.7391   |
| 0.2988        | 22.0  | 143  | 0.7481          | 0.7609   |
| 0.2988        | 22.92 | 149  | 0.9280          | 0.6739   |
| 0.2487        | 24.0  | 156  | 0.6542          | 0.7391   |
| 0.1912        | 24.92 | 162  | 0.7134          | 0.7609   |
| 0.1912        | 26.0  | 169  | 0.8421          | 0.7609   |
| 0.1946        | 26.92 | 175  | 0.7284          | 0.7391   |
| 0.1685        | 28.0  | 182  | 0.7507          | 0.8261   |
| 0.1685        | 28.92 | 188  | 0.7610          | 0.8043   |
| 0.1646        | 30.0  | 195  | 0.8013          | 0.7826   |
| 0.166         | 30.92 | 201  | 0.8803          | 0.7826   |
| 0.166         | 32.0  | 208  | 0.7895          | 0.7391   |
| 0.1372        | 32.92 | 214  | 0.7760          | 0.7174   |
| 0.1424        | 34.0  | 221  | 0.9390          | 0.7174   |
| 0.1424        | 34.92 | 227  | 0.7839          | 0.8043   |
| 0.1399        | 36.0  | 234  | 0.9422          | 0.7609   |
| 0.1238        | 36.92 | 240  | 0.8710          | 0.7174   |
| 0.1238        | 38.0  | 247  | 0.8684          | 0.7826   |
| 0.123         | 38.92 | 253  | 0.8194          | 0.7609   |
| 0.1381        | 40.0  | 260  | 0.9698          | 0.7391   |
| 0.1381        | 40.92 | 266  | 0.8545          | 0.7609   |
| 0.1081        | 42.0  | 273  | 0.9925          | 0.6739   |
| 0.1081        | 42.92 | 279  | 0.9320          | 0.8043   |
| 0.0929        | 44.0  | 286  | 1.0242          | 0.7609   |
| 0.0898        | 44.92 | 292  | 0.9411          | 0.7609   |
| 0.0898        | 46.0  | 299  | 0.8995          | 0.7609   |
| 0.12          | 46.92 | 305  | 0.7741          | 0.7826   |
| 0.1126        | 48.0  | 312  | 0.7122          | 0.8478   |
| 0.1126        | 48.92 | 318  | 0.9099          | 0.7826   |
| 0.1088        | 50.0  | 325  | 1.1148          | 0.6957   |
| 0.0851        | 50.92 | 331  | 0.9297          | 0.8043   |
| 0.0851        | 52.0  | 338  | 0.8801          | 0.8043   |
| 0.1001        | 52.92 | 344  | 0.8428          | 0.8261   |
| 0.0718        | 54.0  | 351  | 0.9721          | 0.7826   |
| 0.0718        | 54.92 | 357  | 0.8771          | 0.8043   |
| 0.0842        | 56.0  | 364  | 0.9982          | 0.7826   |
| 0.1069        | 56.92 | 370  | 1.1083          | 0.7391   |
| 0.1069        | 58.0  | 377  | 0.9072          | 0.7826   |
| 0.0803        | 58.92 | 383  | 0.7979          | 0.8261   |
| 0.0752        | 60.0  | 390  | 0.7489          | 0.8478   |
| 0.0752        | 60.92 | 396  | 0.8023          | 0.8261   |
| 0.0646        | 62.0  | 403  | 0.8027          | 0.8261   |
| 0.0646        | 62.92 | 409  | 0.8275          | 0.7826   |
| 0.0829        | 64.0  | 416  | 0.8587          | 0.8043   |
| 0.0616        | 64.92 | 422  | 0.8870          | 0.8043   |
| 0.0616        | 66.0  | 429  | 0.8928          | 0.8043   |
| 0.0693        | 66.92 | 435  | 0.9289          | 0.7826   |
| 0.0657        | 68.0  | 442  | 0.9604          | 0.7609   |
| 0.0657        | 68.92 | 448  | 0.9560          | 0.7826   |
| 0.0588        | 70.0  | 455  | 0.9544          | 0.7609   |
| 0.0578        | 70.92 | 461  | 0.9419          | 0.7826   |
| 0.0578        | 72.0  | 468  | 0.9474          | 0.7826   |
| 0.0638        | 72.92 | 474  | 0.9540          | 0.7826   |
| 0.0592        | 73.85 | 480  | 0.9549          | 0.7826   |


### Framework versions

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

avanzada leve moderada no dmae