---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-ve-U13-b-80e
  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: 0.8478260869565217
---

<!-- 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-80e

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: 0.6618
- Accuracy: 0.8478

## 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: 0.0003
- 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    | 1.3859          | 0.2391   |
| 1.3857        | 2.0   | 13   | 1.3834          | 0.3261   |
| 1.3857        | 2.92  | 19   | 1.3789          | 0.1957   |
| 1.3767        | 4.0   | 26   | 1.3666          | 0.1739   |
| 1.3227        | 4.92  | 32   | 1.3565          | 0.1522   |
| 1.3227        | 6.0   | 39   | 1.3887          | 0.1087   |
| 1.1987        | 6.92  | 45   | 1.3719          | 0.2174   |
| 1.1071        | 8.0   | 52   | 1.3271          | 0.3043   |
| 1.1071        | 8.92  | 58   | 1.3562          | 0.2609   |
| 0.9926        | 10.0  | 65   | 1.2306          | 0.4130   |
| 0.8721        | 10.92 | 71   | 1.1953          | 0.4565   |
| 0.8721        | 12.0  | 78   | 1.0754          | 0.5652   |
| 0.7746        | 12.92 | 84   | 0.9931          | 0.6739   |
| 0.6859        | 14.0  | 91   | 0.9979          | 0.6739   |
| 0.6859        | 14.92 | 97   | 0.8964          | 0.6957   |
| 0.5777        | 16.0  | 104  | 0.9186          | 0.6522   |
| 0.5136        | 16.92 | 110  | 0.7950          | 0.7609   |
| 0.5136        | 18.0  | 117  | 0.7794          | 0.7391   |
| 0.5019        | 18.92 | 123  | 0.8645          | 0.7174   |
| 0.3879        | 20.0  | 130  | 0.8773          | 0.6957   |
| 0.3879        | 20.92 | 136  | 0.7304          | 0.7609   |
| 0.3532        | 22.0  | 143  | 0.6918          | 0.7609   |
| 0.3532        | 22.92 | 149  | 0.7882          | 0.7609   |
| 0.3288        | 24.0  | 156  | 0.7132          | 0.7609   |
| 0.2573        | 24.92 | 162  | 0.6645          | 0.8043   |
| 0.2573        | 26.0  | 169  | 0.6618          | 0.8478   |
| 0.239         | 26.92 | 175  | 0.6780          | 0.8043   |
| 0.2018        | 28.0  | 182  | 0.8138          | 0.6957   |
| 0.2018        | 28.92 | 188  | 0.8797          | 0.6957   |
| 0.1961        | 30.0  | 195  | 0.8602          | 0.7174   |
| 0.214         | 30.92 | 201  | 0.8188          | 0.7391   |
| 0.214         | 32.0  | 208  | 0.6956          | 0.7609   |
| 0.1596        | 32.92 | 214  | 0.7981          | 0.7391   |
| 0.172         | 34.0  | 221  | 0.6845          | 0.7609   |
| 0.172         | 34.92 | 227  | 0.9340          | 0.7174   |
| 0.1852        | 36.0  | 234  | 0.9548          | 0.6522   |
| 0.1492        | 36.92 | 240  | 0.7747          | 0.7609   |
| 0.1492        | 38.0  | 247  | 0.9907          | 0.6304   |
| 0.1735        | 38.92 | 253  | 0.8040          | 0.7174   |
| 0.1405        | 40.0  | 260  | 0.6946          | 0.7609   |
| 0.1405        | 40.92 | 266  | 0.7019          | 0.7609   |
| 0.1269        | 42.0  | 273  | 0.8246          | 0.7174   |
| 0.1269        | 42.92 | 279  | 0.9238          | 0.6739   |
| 0.1237        | 44.0  | 286  | 0.9354          | 0.6957   |
| 0.1201        | 44.92 | 292  | 0.7543          | 0.7391   |
| 0.1201        | 46.0  | 299  | 0.7151          | 0.7174   |
| 0.1134        | 46.92 | 305  | 0.7284          | 0.7174   |
| 0.1141        | 48.0  | 312  | 0.7791          | 0.7609   |
| 0.1141        | 48.92 | 318  | 0.7824          | 0.7391   |
| 0.1253        | 50.0  | 325  | 0.7319          | 0.7609   |
| 0.0968        | 50.92 | 331  | 0.7151          | 0.7609   |
| 0.0968        | 52.0  | 338  | 0.7662          | 0.7609   |
| 0.0996        | 52.92 | 344  | 0.8086          | 0.7826   |
| 0.0844        | 54.0  | 351  | 0.8921          | 0.7609   |
| 0.0844        | 54.92 | 357  | 0.8782          | 0.7609   |
| 0.1141        | 56.0  | 364  | 0.7864          | 0.7391   |
| 0.1263        | 56.92 | 370  | 0.7125          | 0.7609   |
| 0.1263        | 58.0  | 377  | 0.6758          | 0.7609   |
| 0.0966        | 58.92 | 383  | 0.7243          | 0.7609   |
| 0.0771        | 60.0  | 390  | 0.7090          | 0.7609   |
| 0.0771        | 60.92 | 396  | 0.7157          | 0.7609   |
| 0.0497        | 62.0  | 403  | 0.7549          | 0.7609   |
| 0.0497        | 62.92 | 409  | 0.7806          | 0.7609   |
| 0.0848        | 64.0  | 416  | 0.7902          | 0.7391   |
| 0.0477        | 64.92 | 422  | 0.7684          | 0.7391   |
| 0.0477        | 66.0  | 429  | 0.8038          | 0.6957   |
| 0.0823        | 66.92 | 435  | 0.7503          | 0.6957   |
| 0.0726        | 68.0  | 442  | 0.7634          | 0.7609   |
| 0.0726        | 68.92 | 448  | 0.7860          | 0.7826   |
| 0.0799        | 70.0  | 455  | 0.7630          | 0.7609   |
| 0.067         | 70.92 | 461  | 0.8094          | 0.7391   |
| 0.067         | 72.0  | 468  | 0.7511          | 0.7391   |
| 0.0893        | 72.92 | 474  | 0.7738          | 0.7391   |
| 0.0738        | 73.85 | 480  | 0.7971          | 0.7391   |


### Framework versions

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