---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-ve-U13-b-80b
  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: 0.6521739130434783
---

<!-- 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-80b

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: 1.2197
- Accuracy: 0.6522

## 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: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.3862          | 0.2174   |
| 1.3862        | 2.0   | 13   | 1.3856          | 0.3261   |
| 1.3862        | 2.92  | 19   | 1.3849          | 0.2826   |
| 1.3848        | 4.0   | 26   | 1.3830          | 0.2609   |
| 1.3806        | 4.92  | 32   | 1.3804          | 0.1739   |
| 1.3806        | 6.0   | 39   | 1.3758          | 0.1957   |
| 1.3662        | 6.92  | 45   | 1.3700          | 0.1739   |
| 1.3261        | 8.0   | 52   | 1.3652          | 0.1739   |
| 1.3261        | 8.92  | 58   | 1.3625          | 0.1522   |
| 1.2588        | 10.0  | 65   | 1.3629          | 0.1304   |
| 1.1972        | 10.92 | 71   | 1.3592          | 0.1304   |
| 1.1972        | 12.0  | 78   | 1.3570          | 0.2174   |
| 1.1578        | 12.92 | 84   | 1.3590          | 0.1957   |
| 1.124         | 14.0  | 91   | 1.3731          | 0.2174   |
| 1.124         | 14.92 | 97   | 1.3718          | 0.1522   |
| 1.1045        | 16.0  | 104  | 1.3736          | 0.1739   |
| 1.0703        | 16.92 | 110  | 1.4983          | 0.2174   |
| 1.0703        | 18.0  | 117  | 1.5455          | 0.1739   |
| 1.0663        | 18.92 | 123  | 1.4473          | 0.1739   |
| 1.01          | 20.0  | 130  | 1.4011          | 0.2609   |
| 1.01          | 20.92 | 136  | 1.4053          | 0.2826   |
| 0.9961        | 22.0  | 143  | 1.4186          | 0.2174   |
| 0.9961        | 22.92 | 149  | 1.5168          | 0.2609   |
| 0.9754        | 24.0  | 156  | 1.3873          | 0.2826   |
| 0.9417        | 24.92 | 162  | 1.4656          | 0.3261   |
| 0.9417        | 26.0  | 169  | 1.3499          | 0.2609   |
| 0.9286        | 26.92 | 175  | 1.3902          | 0.3043   |
| 0.9216        | 28.0  | 182  | 1.4819          | 0.3261   |
| 0.9216        | 28.92 | 188  | 1.4133          | 0.3043   |
| 0.8868        | 30.0  | 195  | 1.4124          | 0.4130   |
| 0.8908        | 30.92 | 201  | 1.4421          | 0.3478   |
| 0.8908        | 32.0  | 208  | 1.5085          | 0.3043   |
| 0.8729        | 32.92 | 214  | 1.3854          | 0.3478   |
| 0.8685        | 34.0  | 221  | 1.3264          | 0.3043   |
| 0.8685        | 34.92 | 227  | 1.3947          | 0.3043   |
| 0.8739        | 36.0  | 234  | 1.3455          | 0.3913   |
| 0.8288        | 36.92 | 240  | 1.3621          | 0.3913   |
| 0.8288        | 38.0  | 247  | 1.3875          | 0.3913   |
| 0.8369        | 38.92 | 253  | 1.4274          | 0.3696   |
| 0.8101        | 40.0  | 260  | 1.3251          | 0.4565   |
| 0.8101        | 40.92 | 266  | 1.3039          | 0.4783   |
| 0.8126        | 42.0  | 273  | 1.2523          | 0.5435   |
| 0.8126        | 42.92 | 279  | 1.3060          | 0.5217   |
| 0.7971        | 44.0  | 286  | 1.2678          | 0.5217   |
| 0.7806        | 44.92 | 292  | 1.3332          | 0.5      |
| 0.7806        | 46.0  | 299  | 1.2550          | 0.5652   |
| 0.7899        | 46.92 | 305  | 1.2517          | 0.5870   |
| 0.7602        | 48.0  | 312  | 1.2627          | 0.5870   |
| 0.7602        | 48.92 | 318  | 1.2620          | 0.6087   |
| 0.7748        | 50.0  | 325  | 1.2286          | 0.5652   |
| 0.7613        | 50.92 | 331  | 1.1997          | 0.6087   |
| 0.7613        | 52.0  | 338  | 1.2353          | 0.5870   |
| 0.7514        | 52.92 | 344  | 1.2466          | 0.5870   |
| 0.7581        | 54.0  | 351  | 1.2161          | 0.5870   |
| 0.7581        | 54.92 | 357  | 1.2396          | 0.5435   |
| 0.7401        | 56.0  | 364  | 1.1859          | 0.6087   |
| 0.7421        | 56.92 | 370  | 1.1757          | 0.6304   |
| 0.7421        | 58.0  | 377  | 1.1754          | 0.5870   |
| 0.7261        | 58.92 | 383  | 1.1630          | 0.6304   |
| 0.709         | 60.0  | 390  | 1.2157          | 0.5870   |
| 0.709         | 60.92 | 396  | 1.2124          | 0.6087   |
| 0.7075        | 62.0  | 403  | 1.2095          | 0.6087   |
| 0.7075        | 62.92 | 409  | 1.2543          | 0.5652   |
| 0.7141        | 64.0  | 416  | 1.2210          | 0.6087   |
| 0.6907        | 64.92 | 422  | 1.3190          | 0.5435   |
| 0.6907        | 66.0  | 429  | 1.2197          | 0.6522   |
| 0.7237        | 66.92 | 435  | 1.2365          | 0.5652   |
| 0.6918        | 68.0  | 442  | 1.1570          | 0.6304   |
| 0.6918        | 68.92 | 448  | 1.1790          | 0.6087   |
| 0.7137        | 70.0  | 455  | 1.1968          | 0.6087   |
| 0.6954        | 70.92 | 461  | 1.1959          | 0.6304   |
| 0.6954        | 72.0  | 468  | 1.1782          | 0.6304   |
| 0.6961        | 72.92 | 474  | 1.1935          | 0.5652   |
| 0.6889        | 73.85 | 480  | 1.1835          | 0.6087   |


### Framework versions

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