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

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: 0.5797
- Accuracy: 0.8333

## 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: 42

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9032  | 7    | 1.2066          | 0.55     |
| 1.5038        | 1.9355  | 15   | 1.2167          | 0.4167   |
| 1.1504        | 2.9677  | 23   | 0.8821          | 0.65     |
| 0.8299        | 4.0     | 31   | 0.6489          | 0.7667   |
| 0.8299        | 4.9032  | 38   | 0.5797          | 0.8333   |
| 0.5887        | 5.9355  | 46   | 0.6618          | 0.75     |
| 0.3965        | 6.9677  | 54   | 0.6531          | 0.7833   |
| 0.3089        | 8.0     | 62   | 0.7609          | 0.7      |
| 0.3089        | 8.9032  | 69   | 0.8609          | 0.6833   |
| 0.2393        | 9.9355  | 77   | 0.6910          | 0.7833   |
| 0.1928        | 10.9677 | 85   | 0.7774          | 0.8      |
| 0.1993        | 12.0    | 93   | 0.8424          | 0.7833   |
| 0.165         | 12.9032 | 100  | 0.7478          | 0.7667   |
| 0.165         | 13.9355 | 108  | 0.7573          | 0.75     |
| 0.1117        | 14.9677 | 116  | 0.8059          | 0.8167   |
| 0.1171        | 16.0    | 124  | 0.8982          | 0.7667   |
| 0.0961        | 16.9032 | 131  | 0.9133          | 0.8      |
| 0.0961        | 17.9355 | 139  | 0.9121          | 0.7667   |
| 0.1359        | 18.9677 | 147  | 0.9297          | 0.8      |
| 0.0981        | 20.0    | 155  | 1.0124          | 0.7333   |
| 0.0817        | 20.9032 | 162  | 0.9628          | 0.75     |
| 0.0976        | 21.9355 | 170  | 0.9664          | 0.7667   |
| 0.0976        | 22.9677 | 178  | 0.7980          | 0.8167   |
| 0.0899        | 24.0    | 186  | 0.8366          | 0.7667   |
| 0.1052        | 24.9032 | 193  | 0.9160          | 0.7667   |
| 0.0817        | 25.9355 | 201  | 0.9701          | 0.7667   |
| 0.0817        | 26.9677 | 209  | 0.9995          | 0.75     |
| 0.0886        | 28.0    | 217  | 0.8483          | 0.8      |
| 0.0766        | 28.9032 | 224  | 0.8954          | 0.7833   |
| 0.0923        | 29.9355 | 232  | 0.9606          | 0.7833   |
| 0.0579        | 30.9677 | 240  | 0.9958          | 0.75     |
| 0.0579        | 32.0    | 248  | 0.9665          | 0.7833   |
| 0.0707        | 32.9032 | 255  | 1.0259          | 0.7667   |
| 0.0756        | 33.9355 | 263  | 1.0627          | 0.75     |
| 0.0528        | 34.9677 | 271  | 1.0508          | 0.7667   |
| 0.0528        | 36.0    | 279  | 1.0998          | 0.7667   |
| 0.0706        | 36.9032 | 286  | 1.0694          | 0.75     |
| 0.0658        | 37.9355 | 294  | 1.0561          | 0.7667   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1

avanzada leve moderada no dmae