---
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: 0.7007
- Accuracy: 0.7523

## 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    | 1.3578          | 0.2936   |
| 1.3702        | 1.94  | 15   | 1.3703          | 0.2936   |
| 1.3497        | 2.97  | 23   | 1.3361          | 0.3394   |
| 1.3004        | 4.0   | 31   | 1.2852          | 0.3670   |
| 1.3004        | 4.9   | 38   | 1.2317          | 0.4312   |
| 1.2248        | 5.94  | 46   | 1.1786          | 0.4587   |
| 1.1485        | 6.97  | 54   | 1.1240          | 0.5046   |
| 1.0759        | 8.0   | 62   | 1.0727          | 0.5505   |
| 1.0759        | 8.9   | 69   | 1.0404          | 0.5596   |
| 1.0244        | 9.94  | 77   | 0.9742          | 0.6239   |
| 0.9782        | 10.97 | 85   | 0.9374          | 0.6422   |
| 0.9359        | 12.0  | 93   | 0.9197          | 0.6789   |
| 0.9051        | 12.9  | 100  | 0.8753          | 0.6881   |
| 0.9051        | 13.94 | 108  | 0.8679          | 0.6972   |
| 0.8652        | 14.97 | 116  | 0.8316          | 0.7156   |
| 0.8336        | 16.0  | 124  | 0.8222          | 0.6972   |
| 0.8177        | 16.9  | 131  | 0.8178          | 0.6972   |
| 0.8177        | 17.94 | 139  | 0.7818          | 0.7339   |
| 0.8077        | 18.97 | 147  | 0.7627          | 0.7339   |
| 0.7796        | 20.0  | 155  | 0.7478          | 0.7339   |
| 0.7673        | 20.9  | 162  | 0.7415          | 0.7431   |
| 0.7445        | 21.94 | 170  | 0.7414          | 0.7156   |
| 0.7445        | 22.97 | 178  | 0.7375          | 0.7156   |
| 0.7413        | 24.0  | 186  | 0.7354          | 0.7156   |
| 0.739         | 24.9  | 193  | 0.7110          | 0.7431   |
| 0.6992        | 25.94 | 201  | 0.7121          | 0.7339   |
| 0.6992        | 26.97 | 209  | 0.7044          | 0.7431   |
| 0.7111        | 28.0  | 217  | 0.6947          | 0.7339   |
| 0.7013        | 28.9  | 224  | 0.7007          | 0.7523   |
| 0.712         | 29.94 | 232  | 0.6793          | 0.7431   |
| 0.671         | 30.97 | 240  | 0.6808          | 0.7431   |
| 0.671         | 32.0  | 248  | 0.6821          | 0.7339   |
| 0.6862        | 32.9  | 255  | 0.6705          | 0.7339   |
| 0.6606        | 33.94 | 263  | 0.6784          | 0.7431   |
| 0.6667        | 34.97 | 271  | 0.6764          | 0.7523   |
| 0.6667        | 36.0  | 279  | 0.6717          | 0.7523   |
| 0.6687        | 36.13 | 280  | 0.6736          | 0.7523   |


### Framework versions

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