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# swiftformer-xs-dmae-va-U5-42

This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0447
- Accuracy: 0.55

## 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: 42

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 1.3144          | 0.4833   |
| 1.3947        | 1.94  | 15   | 1.3154          | 0.4      |
| 1.3947        | 2.97  | 23   | 1.2849          | 0.4167   |
| 1.3608        | 4.0   | 31   | 1.2512          | 0.4667   |
| 1.3048        | 4.9   | 38   | 1.2340          | 0.55     |
| 1.3048        | 5.94  | 46   | 1.2118          | 0.5833   |
| 1.2456        | 6.97  | 54   | 1.2077          | 0.55     |
| 1.186         | 8.0   | 62   | 1.1672          | 0.5333   |
| 1.186         | 8.9   | 69   | 1.1565          | 0.6167   |
| 1.1218        | 9.94  | 77   | 1.1532          | 0.5833   |
| 1.0731        | 10.97 | 85   | 1.1304          | 0.5833   |
| 1.0731        | 12.0  | 93   | 1.1664          | 0.5167   |
| 1.0135        | 12.9  | 100  | 1.1222          | 0.55     |
| 0.9783        | 13.94 | 108  | 1.1404          | 0.5333   |
| 0.9783        | 14.97 | 116  | 1.1022          | 0.5833   |
| 0.9195        | 16.0  | 124  | 1.0996          | 0.55     |
| 0.9195        | 16.9  | 131  | 1.0715          | 0.6      |
| 0.9023        | 17.94 | 139  | 1.0779          | 0.5833   |
| 0.8575        | 18.97 | 147  | 1.0797          | 0.5667   |
| 0.8575        | 20.0  | 155  | 1.0508          | 0.5833   |
| 0.8519        | 20.9  | 162  | 1.0500          | 0.5833   |
| 0.8098        | 21.94 | 170  | 1.0212          | 0.5667   |
| 0.8098        | 22.97 | 178  | 1.0041          | 0.5833   |
| 0.8018        | 24.0  | 186  | 1.0197          | 0.5667   |
| 0.7709        | 24.9  | 193  | 1.0283          | 0.5333   |
| 0.7709        | 25.94 | 201  | 1.0303          | 0.55     |
| 0.7642        | 26.97 | 209  | 1.0100          | 0.5833   |
| 0.7322        | 28.0  | 217  | 1.0475          | 0.5333   |
| 0.7322        | 28.9  | 224  | 1.0667          | 0.55     |
| 0.7245        | 29.94 | 232  | 1.0743          | 0.55     |
| 0.7254        | 30.97 | 240  | 1.0416          | 0.5333   |
| 0.7254        | 32.0  | 248  | 1.0664          | 0.5667   |
| 0.7201        | 32.9  | 255  | 1.0393          | 0.55     |
| 0.7201        | 33.94 | 263  | 1.0284          | 0.55     |
| 0.6968        | 34.97 | 271  | 1.0420          | 0.55     |
| 0.7073        | 36.0  | 279  | 1.0396          | 0.5333   |
| 0.7073        | 36.9  | 286  | 1.0640          | 0.55     |
| 0.6891        | 37.94 | 294  | 1.0447          | 0.55     |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

avanzada leve moderada no dmae