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

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5453
- 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 0.5397          | 0.85     |
| 0.3809        | 1.94  | 15   | 0.5212          | 0.85     |
| 0.316         | 2.97  | 23   | 0.5690          | 0.8      |
| 0.2892        | 4.0   | 31   | 0.6506          | 0.7667   |
| 0.2892        | 4.9   | 38   | 0.5529          | 0.8333   |
| 0.2127        | 5.94  | 46   | 0.4987          | 0.8333   |
| 0.1712        | 6.97  | 54   | 0.5859          | 0.8167   |
| 0.1539        | 8.0   | 62   | 0.5937          | 0.8      |
| 0.1539        | 8.9   | 69   | 0.5103          | 0.8333   |
| 0.1378        | 9.94  | 77   | 0.6844          | 0.7833   |
| 0.1144        | 10.97 | 85   | 0.5357          | 0.85     |
| 0.1055        | 12.0  | 93   | 0.6695          | 0.8      |
| 0.1093        | 12.9  | 100  | 0.5593          | 0.85     |
| 0.1093        | 13.94 | 108  | 0.5453          | 0.8667   |
| 0.0956        | 14.97 | 116  | 0.6144          | 0.85     |
| 0.1057        | 16.0  | 124  | 0.5067          | 0.8333   |
| 0.0907        | 16.9  | 131  | 0.6570          | 0.8      |
| 0.0907        | 17.94 | 139  | 0.5343          | 0.8667   |
| 0.1184        | 18.97 | 147  | 0.5516          | 0.8667   |
| 0.1014        | 20.0  | 155  | 0.8173          | 0.7667   |
| 0.0997        | 20.9  | 162  | 0.6839          | 0.8167   |
| 0.1067        | 21.94 | 170  | 0.5552          | 0.8667   |
| 0.1067        | 22.97 | 178  | 0.5475          | 0.8667   |
| 0.082         | 24.0  | 186  | 0.5567          | 0.85     |
| 0.0852        | 24.9  | 193  | 0.6374          | 0.8167   |
| 0.0815        | 25.94 | 201  | 0.6486          | 0.8167   |
| 0.0815        | 26.97 | 209  | 0.6218          | 0.8167   |
| 0.0917        | 27.1  | 210  | 0.6209          | 0.8167   |


### Framework versions

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

avanzada leve moderada no dmae