---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swiftformer-xs-dmae-va-U-40
  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-40

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: 0.6423
- Accuracy: 0.8165

## 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    | 1.3883          | 0.3211   |
| 1.4011        | 1.94  | 15   | 1.3383          | 0.3578   |
| 1.3646        | 2.97  | 23   | 1.2802          | 0.4404   |
| 1.315         | 4.0   | 31   | 1.2194          | 0.4495   |
| 1.315         | 4.9   | 38   | 1.1718          | 0.5229   |
| 1.2634        | 5.94  | 46   | 1.1279          | 0.5046   |
| 1.1949        | 6.97  | 54   | 1.0761          | 0.5872   |
| 1.1136        | 8.0   | 62   | 1.0224          | 0.6330   |
| 1.1136        | 8.9   | 69   | 0.9976          | 0.6239   |
| 1.0824        | 9.94  | 77   | 0.9518          | 0.6606   |
| 1.0212        | 10.97 | 85   | 0.9117          | 0.6697   |
| 0.9566        | 12.0  | 93   | 0.8973          | 0.6881   |
| 0.935         | 12.9  | 100  | 0.8705          | 0.7064   |
| 0.935         | 13.94 | 108  | 0.8559          | 0.7156   |
| 0.8826        | 14.97 | 116  | 0.8371          | 0.7156   |
| 0.8688        | 16.0  | 124  | 0.8252          | 0.7156   |
| 0.8436        | 16.9  | 131  | 0.8211          | 0.6972   |
| 0.8436        | 17.94 | 139  | 0.8040          | 0.7339   |
| 0.8155        | 18.97 | 147  | 0.7625          | 0.7431   |
| 0.7831        | 20.0  | 155  | 0.7452          | 0.7431   |
| 0.7826        | 20.9  | 162  | 0.7279          | 0.7431   |
| 0.7499        | 21.94 | 170  | 0.7148          | 0.7431   |
| 0.7499        | 22.97 | 178  | 0.7061          | 0.7523   |
| 0.7539        | 24.0  | 186  | 0.7026          | 0.7523   |
| 0.7453        | 24.9  | 193  | 0.6819          | 0.7890   |
| 0.7174        | 25.94 | 201  | 0.6837          | 0.7706   |
| 0.7174        | 26.97 | 209  | 0.6743          | 0.7798   |
| 0.7083        | 28.0  | 217  | 0.6706          | 0.7798   |
| 0.6813        | 28.9  | 224  | 0.6644          | 0.8073   |
| 0.7107        | 29.94 | 232  | 0.6423          | 0.8165   |
| 0.6912        | 30.97 | 240  | 0.6419          | 0.7890   |
| 0.6912        | 32.0  | 248  | 0.6465          | 0.7890   |
| 0.7031        | 32.9  | 255  | 0.6346          | 0.8073   |
| 0.6647        | 33.94 | 263  | 0.6347          | 0.8073   |
| 0.6799        | 34.97 | 271  | 0.6476          | 0.7982   |
| 0.6799        | 36.0  | 279  | 0.6429          | 0.7982   |
| 0.6774        | 36.13 | 280  | 0.6518          | 0.7890   |


### Framework versions

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