---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swiftformer-xs-dmae-va-U-SF
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# swiftformer-xs-dmae-va-U-SF

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: 0.6987
- Accuracy: 0.7431

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 1.3887          | 0.3119   |
| 1.4383        | 1.94  | 15   | 1.3440          | 0.4128   |
| 1.3956        | 2.97  | 23   | 1.3159          | 0.3761   |
| 1.36          | 4.0   | 31   | 1.2907          | 0.3853   |
| 1.36          | 4.9   | 38   | 1.2488          | 0.4404   |
| 1.2912        | 5.94  | 46   | 1.2129          | 0.4037   |
| 1.2387        | 6.97  | 54   | 1.1734          | 0.4679   |
| 1.1607        | 8.0   | 62   | 1.1436          | 0.5138   |
| 1.1607        | 8.9   | 69   | 1.0991          | 0.4954   |
| 1.1224        | 9.94  | 77   | 1.0479          | 0.5505   |
| 1.0547        | 10.97 | 85   | 0.9993          | 0.5963   |
| 1.0137        | 12.0  | 93   | 0.9860          | 0.6147   |
| 0.9652        | 12.9  | 100  | 0.9698          | 0.6147   |
| 0.9652        | 13.94 | 108  | 0.9519          | 0.6055   |
| 0.9217        | 14.97 | 116  | 0.9242          | 0.6055   |
| 0.9122        | 16.0  | 124  | 0.9062          | 0.6147   |
| 0.8763        | 16.9  | 131  | 0.8873          | 0.6422   |
| 0.8763        | 17.94 | 139  | 0.8477          | 0.6514   |
| 0.8471        | 18.97 | 147  | 0.8427          | 0.6514   |
| 0.8331        | 20.0  | 155  | 0.8257          | 0.6881   |
| 0.8167        | 20.9  | 162  | 0.8025          | 0.6881   |
| 0.8022        | 21.94 | 170  | 0.8011          | 0.6972   |
| 0.8022        | 22.97 | 178  | 0.8078          | 0.6972   |
| 0.7996        | 24.0  | 186  | 0.7920          | 0.7064   |
| 0.7962        | 24.9  | 193  | 0.7604          | 0.7248   |
| 0.7268        | 25.94 | 201  | 0.7597          | 0.6972   |
| 0.7268        | 26.97 | 209  | 0.7462          | 0.6972   |
| 0.7477        | 28.0  | 217  | 0.7316          | 0.7064   |
| 0.7411        | 28.9  | 224  | 0.7275          | 0.7523   |
| 0.7415        | 29.94 | 232  | 0.7210          | 0.7248   |
| 0.7159        | 30.97 | 240  | 0.7271          | 0.7248   |
| 0.7159        | 32.0  | 248  | 0.7005          | 0.7431   |
| 0.7322        | 32.9  | 255  | 0.7012          | 0.7431   |
| 0.7124        | 33.94 | 263  | 0.7052          | 0.7523   |
| 0.7194        | 34.97 | 271  | 0.6964          | 0.7615   |
| 0.7194        | 36.0  | 279  | 0.7007          | 0.7523   |
| 0.6903        | 36.13 | 280  | 0.6987          | 0.7431   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1