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# vit-base-patch16-224-dmae-va-U5-100bcont-i

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5017
- Accuracy: 0.8667

## 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: 0.05
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 0.5017          | 0.8667   |
| 0.3168        | 1.94  | 15   | 0.5969          | 0.8      |
| 0.2613        | 2.97  | 23   | 0.5431          | 0.8167   |
| 0.2218        | 4.0   | 31   | 0.7111          | 0.7833   |
| 0.2218        | 4.9   | 38   | 0.5085          | 0.85     |
| 0.1757        | 5.94  | 46   | 0.5931          | 0.8167   |
| 0.1668        | 6.97  | 54   | 0.5063          | 0.85     |
| 0.1453        | 8.0   | 62   | 0.4997          | 0.85     |
| 0.1453        | 8.9   | 69   | 0.5403          | 0.85     |
| 0.123         | 9.03  | 70   | 0.5403          | 0.85     |


### Framework versions

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

avanzada leve moderada no dmae