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

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: 0.7864
- Accuracy: 0.75

## 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: 0.0002
- 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    | 1.1573          | 0.6167   |
| 1.1018        | 1.94  | 15   | 1.1844          | 0.5667   |
| 1.1018        | 2.97  | 23   | 1.1120          | 0.55     |
| 0.9952        | 4.0   | 31   | 0.9493          | 0.6333   |
| 0.8441        | 4.9   | 38   | 0.9586          | 0.65     |
| 0.8441        | 5.94  | 46   | 1.0176          | 0.6167   |
| 0.7045        | 6.97  | 54   | 0.8787          | 0.6667   |
| 0.5583        | 8.0   | 62   | 1.3863          | 0.5333   |
| 0.5583        | 8.9   | 69   | 0.9727          | 0.6667   |
| 0.457         | 9.94  | 77   | 1.0685          | 0.6167   |
| 0.3699        | 10.97 | 85   | 1.1291          | 0.6667   |
| 0.3699        | 12.0  | 93   | 0.9419          | 0.6667   |
| 0.3095        | 12.9  | 100  | 0.8806          | 0.6333   |
| 0.2544        | 13.94 | 108  | 0.8804          | 0.7167   |
| 0.2544        | 14.97 | 116  | 0.8399          | 0.65     |
| 0.2175        | 16.0  | 124  | 0.8857          | 0.6333   |
| 0.2175        | 16.9  | 131  | 0.9544          | 0.6667   |
| 0.2152        | 17.94 | 139  | 1.0697          | 0.6833   |
| 0.2011        | 18.97 | 147  | 1.0718          | 0.6667   |
| 0.2011        | 20.0  | 155  | 1.0276          | 0.6667   |
| 0.182         | 20.9  | 162  | 0.8614          | 0.6833   |
| 0.1591        | 21.94 | 170  | 0.7872          | 0.6833   |
| 0.1591        | 22.97 | 178  | 1.0134          | 0.65     |
| 0.1557        | 24.0  | 186  | 0.9191          | 0.65     |
| 0.1476        | 24.9  | 193  | 0.8978          | 0.65     |
| 0.1476        | 25.94 | 201  | 0.8872          | 0.7      |
| 0.1587        | 26.97 | 209  | 1.0397          | 0.7      |
| 0.1082        | 28.0  | 217  | 0.9320          | 0.6833   |
| 0.1082        | 28.9  | 224  | 0.8857          | 0.6667   |
| 0.1345        | 29.94 | 232  | 0.8767          | 0.6667   |
| 0.1308        | 30.97 | 240  | 0.8945          | 0.6833   |
| 0.1308        | 32.0  | 248  | 0.9545          | 0.6833   |
| 0.1348        | 32.9  | 255  | 0.9330          | 0.7      |
| 0.1348        | 33.94 | 263  | 0.9131          | 0.7167   |
| 0.1162        | 34.97 | 271  | 0.8424          | 0.7167   |
| 0.1134        | 36.0  | 279  | 0.8275          | 0.6833   |
| 0.1134        | 36.9  | 286  | 0.8106          | 0.7333   |
| 0.1108        | 37.94 | 294  | 0.7864          | 0.75     |


### Framework versions

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

avanzada leve moderada no dmae