---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swiftformer-xs-dmae-va-U-80
  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-80

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: 0.6494
- 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    | 1.3781          | 0.3486   |
| 1.3901        | 1.94  | 15   | 1.3538          | 0.3303   |
| 1.3561        | 2.97  | 23   | 1.3091          | 0.3761   |
| 1.2933        | 4.0   | 31   | 1.2623          | 0.4220   |
| 1.2933        | 4.9   | 38   | 1.2065          | 0.5138   |
| 1.2274        | 5.94  | 46   | 1.1353          | 0.5413   |
| 1.1686        | 6.97  | 54   | 1.0854          | 0.6147   |
| 1.097         | 8.0   | 62   | 1.0489          | 0.6330   |
| 1.097         | 8.9   | 69   | 1.0185          | 0.6606   |
| 1.0349        | 9.94  | 77   | 0.9682          | 0.6422   |
| 1.0161        | 10.97 | 85   | 0.9511          | 0.6055   |
| 0.9633        | 12.0  | 93   | 0.9009          | 0.6606   |
| 0.939         | 12.9  | 100  | 0.9055          | 0.6514   |
| 0.939         | 13.94 | 108  | 0.8781          | 0.6697   |
| 0.9036        | 14.97 | 116  | 0.8494          | 0.7248   |
| 0.8687        | 16.0  | 124  | 0.8503          | 0.6789   |
| 0.8535        | 16.9  | 131  | 0.8164          | 0.7248   |
| 0.8535        | 17.94 | 139  | 0.7883          | 0.7615   |
| 0.8306        | 18.97 | 147  | 0.7667          | 0.7615   |
| 0.8047        | 20.0  | 155  | 0.7600          | 0.7523   |
| 0.7735        | 20.9  | 162  | 0.7331          | 0.7615   |
| 0.784         | 21.94 | 170  | 0.7295          | 0.7523   |
| 0.784         | 22.97 | 178  | 0.7281          | 0.7431   |
| 0.7596        | 24.0  | 186  | 0.7045          | 0.7615   |
| 0.7609        | 24.9  | 193  | 0.6915          | 0.7706   |
| 0.7307        | 25.94 | 201  | 0.6970          | 0.8073   |
| 0.7307        | 26.97 | 209  | 0.6796          | 0.7615   |
| 0.7263        | 28.0  | 217  | 0.6615          | 0.7706   |
| 0.6933        | 28.9  | 224  | 0.6628          | 0.7798   |
| 0.6914        | 29.94 | 232  | 0.6596          | 0.8073   |
| 0.7192        | 30.97 | 240  | 0.6453          | 0.7982   |
| 0.7192        | 32.0  | 248  | 0.6569          | 0.7798   |
| 0.6956        | 32.9  | 255  | 0.6494          | 0.8165   |
| 0.7037        | 33.94 | 263  | 0.6478          | 0.8073   |
| 0.669         | 34.97 | 271  | 0.6415          | 0.7798   |
| 0.669         | 36.0  | 279  | 0.6441          | 0.7890   |
| 0.6715        | 36.13 | 280  | 0.6445          | 0.7798   |


### Framework versions

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