---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-ve-U13-b-80
  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: 0.8695652173913043
---

<!-- 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-80

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: 0.6163
- Accuracy: 0.8696

## 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: 0.1
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.4461          | 0.1087   |
| 1.3993        | 2.0   | 13   | 1.4435          | 0.1087   |
| 1.3993        | 2.92  | 19   | 1.4389          | 0.1087   |
| 1.3849        | 4.0   | 26   | 1.4284          | 0.1087   |
| 1.3287        | 4.92  | 32   | 1.4223          | 0.1304   |
| 1.3287        | 6.0   | 39   | 1.4647          | 0.1087   |
| 1.2128        | 6.92  | 45   | 1.4184          | 0.1739   |
| 1.122         | 8.0   | 52   | 1.3262          | 0.1957   |
| 1.122         | 8.92  | 58   | 1.3298          | 0.1957   |
| 1.0062        | 10.0  | 65   | 1.2035          | 0.3696   |
| 0.872         | 10.92 | 71   | 1.3667          | 0.3261   |
| 0.872         | 12.0  | 78   | 1.2013          | 0.4348   |
| 0.814         | 12.92 | 84   | 0.9996          | 0.6957   |
| 0.7228        | 14.0  | 91   | 0.9706          | 0.7609   |
| 0.7228        | 14.92 | 97   | 0.9295          | 0.7391   |
| 0.6473        | 16.0  | 104  | 0.8988          | 0.7174   |
| 0.5696        | 16.92 | 110  | 0.9612          | 0.6739   |
| 0.5696        | 18.0  | 117  | 0.8713          | 0.7609   |
| 0.5546        | 18.92 | 123  | 0.8050          | 0.7609   |
| 0.4747        | 20.0  | 130  | 0.7725          | 0.7609   |
| 0.4747        | 20.92 | 136  | 0.7933          | 0.6957   |
| 0.4393        | 22.0  | 143  | 0.7665          | 0.6957   |
| 0.4393        | 22.92 | 149  | 0.7886          | 0.7174   |
| 0.4077        | 24.0  | 156  | 0.7824          | 0.7391   |
| 0.3326        | 24.92 | 162  | 0.7021          | 0.7391   |
| 0.3326        | 26.0  | 169  | 0.6346          | 0.8261   |
| 0.315         | 26.92 | 175  | 0.6163          | 0.8696   |
| 0.2729        | 28.0  | 182  | 0.6938          | 0.8043   |
| 0.2729        | 28.92 | 188  | 0.7417          | 0.8043   |
| 0.2218        | 30.0  | 195  | 0.6669          | 0.7826   |
| 0.2499        | 30.92 | 201  | 0.7111          | 0.7174   |
| 0.2499        | 32.0  | 208  | 0.6730          | 0.7826   |
| 0.2218        | 32.92 | 214  | 0.6512          | 0.8043   |
| 0.2037        | 34.0  | 221  | 0.7165          | 0.7391   |
| 0.2037        | 34.92 | 227  | 0.6300          | 0.8261   |
| 0.2367        | 36.0  | 234  | 0.7421          | 0.7826   |
| 0.1835        | 36.92 | 240  | 0.6644          | 0.8043   |
| 0.1835        | 38.0  | 247  | 0.6251          | 0.8261   |
| 0.2073        | 38.92 | 253  | 0.6431          | 0.7826   |
| 0.1643        | 40.0  | 260  | 0.6348          | 0.8043   |
| 0.1643        | 40.92 | 266  | 0.6192          | 0.8043   |
| 0.1685        | 42.0  | 273  | 0.6753          | 0.8043   |
| 0.1685        | 42.92 | 279  | 0.7440          | 0.7826   |
| 0.1539        | 44.0  | 286  | 0.7505          | 0.8043   |
| 0.1658        | 44.92 | 292  | 0.6331          | 0.8261   |
| 0.1658        | 46.0  | 299  | 0.6550          | 0.8043   |
| 0.1596        | 46.92 | 305  | 0.6824          | 0.8043   |
| 0.1534        | 48.0  | 312  | 0.6971          | 0.8043   |
| 0.1534        | 48.92 | 318  | 0.6347          | 0.8261   |
| 0.1677        | 50.0  | 325  | 0.6392          | 0.8261   |
| 0.1453        | 50.92 | 331  | 0.6369          | 0.8043   |
| 0.1453        | 52.0  | 338  | 0.6230          | 0.7826   |
| 0.1385        | 52.92 | 344  | 0.6432          | 0.7609   |
| 0.1221        | 54.0  | 351  | 0.6757          | 0.7391   |
| 0.1221        | 54.92 | 357  | 0.7383          | 0.7609   |
| 0.1433        | 56.0  | 364  | 0.7100          | 0.7609   |
| 0.1567        | 56.92 | 370  | 0.6862          | 0.7609   |
| 0.1567        | 58.0  | 377  | 0.6654          | 0.7609   |
| 0.1361        | 58.92 | 383  | 0.6665          | 0.7826   |
| 0.1157        | 60.0  | 390  | 0.6439          | 0.7826   |
| 0.1157        | 60.92 | 396  | 0.6306          | 0.8261   |
| 0.0934        | 62.0  | 403  | 0.6546          | 0.8043   |
| 0.0934        | 62.92 | 409  | 0.6651          | 0.8043   |
| 0.1123        | 64.0  | 416  | 0.6568          | 0.7609   |
| 0.0855        | 64.92 | 422  | 0.6507          | 0.7609   |
| 0.0855        | 66.0  | 429  | 0.6667          | 0.8043   |
| 0.1135        | 66.92 | 435  | 0.6516          | 0.7826   |
| 0.0932        | 68.0  | 442  | 0.6596          | 0.8043   |
| 0.0932        | 68.92 | 448  | 0.6772          | 0.8043   |
| 0.1228        | 70.0  | 455  | 0.6526          | 0.7609   |
| 0.0878        | 70.92 | 461  | 0.6731          | 0.8261   |
| 0.0878        | 72.0  | 468  | 0.6351          | 0.7826   |
| 0.1073        | 72.92 | 474  | 0.6269          | 0.7826   |
| 0.1028        | 73.85 | 480  | 0.6743          | 0.7826   |


### Framework versions

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