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# beit-base-patch16-224-dmae-va-U5-42C

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9081
- Accuracy: 0.65

## 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: 1e-06
- 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: 42

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 2.0475          | 0.1      |
| 2.0435        | 1.94  | 15   | 1.8868          | 0.1      |
| 1.9821        | 2.97  | 23   | 1.6588          | 0.1333   |
| 1.7075        | 4.0   | 31   | 1.4345          | 0.3      |
| 1.7075        | 4.9   | 38   | 1.2973          | 0.4      |
| 1.5153        | 5.94  | 46   | 1.2245          | 0.4167   |
| 1.4239        | 6.97  | 54   | 1.1969          | 0.5167   |
| 1.354         | 8.0   | 62   | 1.1733          | 0.4833   |
| 1.354         | 8.9   | 69   | 1.1552          | 0.5167   |
| 1.2885        | 9.94  | 77   | 1.1274          | 0.55     |
| 1.2549        | 10.97 | 85   | 1.1119          | 0.55     |
| 1.2378        | 12.0  | 93   | 1.1023          | 0.5667   |
| 1.1994        | 12.9  | 100  | 1.0860          | 0.5833   |
| 1.1994        | 13.94 | 108  | 1.0694          | 0.6      |
| 1.1535        | 14.97 | 116  | 1.0548          | 0.6167   |
| 1.1354        | 16.0  | 124  | 1.0402          | 0.6167   |
| 1.1031        | 16.9  | 131  | 1.0266          | 0.6167   |
| 1.1031        | 17.94 | 139  | 1.0156          | 0.6167   |
| 1.1006        | 18.97 | 147  | 1.0024          | 0.6167   |
| 1.0655        | 20.0  | 155  | 0.9867          | 0.6167   |
| 1.0439        | 20.9  | 162  | 0.9770          | 0.6167   |
| 1.0335        | 21.94 | 170  | 0.9662          | 0.6      |
| 1.0335        | 22.97 | 178  | 0.9590          | 0.6      |
| 1.0152        | 24.0  | 186  | 0.9504          | 0.6167   |
| 1.01          | 24.9  | 193  | 0.9433          | 0.6333   |
| 0.9779        | 25.94 | 201  | 0.9395          | 0.6333   |
| 0.9779        | 26.97 | 209  | 0.9354          | 0.65     |
| 0.9792        | 28.0  | 217  | 0.9292          | 0.65     |
| 0.9591        | 28.9  | 224  | 0.9257          | 0.65     |
| 0.9643        | 29.94 | 232  | 0.9211          | 0.65     |
| 0.9453        | 30.97 | 240  | 0.9172          | 0.65     |
| 0.9453        | 32.0  | 248  | 0.9150          | 0.65     |
| 0.938         | 32.9  | 255  | 0.9129          | 0.65     |
| 0.9206        | 33.94 | 263  | 0.9105          | 0.65     |
| 0.9412        | 34.97 | 271  | 0.9096          | 0.65     |
| 0.9412        | 36.0  | 279  | 0.9087          | 0.65     |
| 0.9363        | 36.9  | 286  | 0.9083          | 0.65     |
| 0.9356        | 37.94 | 294  | 0.9081          | 0.65     |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2

avanzada leve moderada no dmae