---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-ve-U13-b-80c
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8043478260869565
---

<!-- 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-ve-U13-b-80c

This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co./MBZUAI/swiftformer-xs) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7032
- Accuracy: 0.8043

## 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: 0.15
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.3860          | 0.2391   |
| 1.3859        | 2.0   | 13   | 1.3844          | 0.3043   |
| 1.3859        | 2.92  | 19   | 1.3820          | 0.1957   |
| 1.381         | 4.0   | 26   | 1.3746          | 0.1739   |
| 1.3573        | 4.92  | 32   | 1.3643          | 0.1957   |
| 1.3573        | 6.0   | 39   | 1.3561          | 0.1522   |
| 1.2692        | 6.92  | 45   | 1.3583          | 0.1522   |
| 1.1682        | 8.0   | 52   | 1.3623          | 0.1739   |
| 1.1682        | 8.92  | 58   | 1.3296          | 0.2609   |
| 1.1005        | 10.0  | 65   | 1.2663          | 0.3913   |
| 0.9884        | 10.92 | 71   | 1.3160          | 0.3696   |
| 0.9884        | 12.0  | 78   | 1.1806          | 0.4783   |
| 0.9111        | 12.92 | 84   | 1.1560          | 0.6087   |
| 0.8464        | 14.0  | 91   | 1.1350          | 0.5870   |
| 0.8464        | 14.92 | 97   | 1.0768          | 0.6304   |
| 0.7768        | 16.0  | 104  | 0.9707          | 0.6087   |
| 0.6754        | 16.92 | 110  | 0.9544          | 0.6522   |
| 0.6754        | 18.0  | 117  | 0.9885          | 0.6739   |
| 0.657         | 18.92 | 123  | 0.8578          | 0.6957   |
| 0.5408        | 20.0  | 130  | 0.7794          | 0.7391   |
| 0.5408        | 20.92 | 136  | 0.8072          | 0.7391   |
| 0.5094        | 22.0  | 143  | 0.7917          | 0.6739   |
| 0.5094        | 22.92 | 149  | 0.7975          | 0.6739   |
| 0.4546        | 24.0  | 156  | 0.7583          | 0.7609   |
| 0.3722        | 24.92 | 162  | 0.7074          | 0.7826   |
| 0.3722        | 26.0  | 169  | 0.6909          | 0.7391   |
| 0.3494        | 26.92 | 175  | 0.7032          | 0.8043   |
| 0.3092        | 28.0  | 182  | 0.8149          | 0.7826   |
| 0.3092        | 28.92 | 188  | 0.7898          | 0.7826   |
| 0.2643        | 30.0  | 195  | 0.7312          | 0.8043   |
| 0.2659        | 30.92 | 201  | 0.7598          | 0.7174   |
| 0.2659        | 32.0  | 208  | 0.7531          | 0.7609   |
| 0.2298        | 32.92 | 214  | 0.6877          | 0.8043   |
| 0.2147        | 34.0  | 221  | 0.6864          | 0.8043   |
| 0.2147        | 34.92 | 227  | 0.7656          | 0.7391   |
| 0.2457        | 36.0  | 234  | 0.8494          | 0.7391   |
| 0.1905        | 36.92 | 240  | 0.7319          | 0.7609   |
| 0.1905        | 38.0  | 247  | 0.8290          | 0.6957   |
| 0.2073        | 38.92 | 253  | 0.7963          | 0.7609   |
| 0.1603        | 40.0  | 260  | 0.8693          | 0.6957   |
| 0.1603        | 40.92 | 266  | 0.7138          | 0.8043   |
| 0.1852        | 42.0  | 273  | 0.7274          | 0.7609   |
| 0.1852        | 42.92 | 279  | 0.8353          | 0.6739   |
| 0.1641        | 44.0  | 286  | 0.9382          | 0.6957   |
| 0.1568        | 44.92 | 292  | 0.8655          | 0.7174   |
| 0.1568        | 46.0  | 299  | 0.7621          | 0.7391   |
| 0.1498        | 46.92 | 305  | 0.7944          | 0.7174   |
| 0.1563        | 48.0  | 312  | 0.8433          | 0.6957   |
| 0.1563        | 48.92 | 318  | 0.8633          | 0.7609   |
| 0.1554        | 50.0  | 325  | 0.8543          | 0.7391   |
| 0.1316        | 50.92 | 331  | 0.9127          | 0.7174   |
| 0.1316        | 52.0  | 338  | 0.9248          | 0.6957   |
| 0.1264        | 52.92 | 344  | 0.9349          | 0.6957   |
| 0.1082        | 54.0  | 351  | 0.9785          | 0.6739   |
| 0.1082        | 54.92 | 357  | 1.0165          | 0.6739   |
| 0.1366        | 56.0  | 364  | 0.8369          | 0.6957   |
| 0.1546        | 56.92 | 370  | 0.8372          | 0.7174   |
| 0.1546        | 58.0  | 377  | 0.8596          | 0.6957   |
| 0.1218        | 58.92 | 383  | 0.8054          | 0.7174   |
| 0.1162        | 60.0  | 390  | 0.7963          | 0.7391   |
| 0.1162        | 60.92 | 396  | 0.7953          | 0.7391   |
| 0.0876        | 62.0  | 403  | 0.8229          | 0.7391   |
| 0.0876        | 62.92 | 409  | 0.8365          | 0.7391   |
| 0.1032        | 64.0  | 416  | 0.8162          | 0.7609   |
| 0.0825        | 64.92 | 422  | 0.8646          | 0.7391   |
| 0.0825        | 66.0  | 429  | 0.9135          | 0.7391   |
| 0.1119        | 66.92 | 435  | 0.9164          | 0.7391   |
| 0.0949        | 68.0  | 442  | 0.9232          | 0.7391   |
| 0.0949        | 68.92 | 448  | 0.9381          | 0.7391   |
| 0.1227        | 70.0  | 455  | 0.8998          | 0.7391   |
| 0.0872        | 70.92 | 461  | 0.9632          | 0.7174   |
| 0.0872        | 72.0  | 468  | 0.8566          | 0.7174   |
| 0.1033        | 72.92 | 474  | 0.8909          | 0.7174   |
| 0.0876        | 73.85 | 480  | 0.8869          | 0.7609   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0