---
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: 0.8260869565217391
---

<!-- 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: 0.7132
- Accuracy: 0.8261

## 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    | 1.3859          | 0.2391   |
| 1.3857        | 2.0   | 13   | 1.3834          | 0.2826   |
| 1.3857        | 2.92  | 19   | 1.3789          | 0.1957   |
| 1.3767        | 4.0   | 26   | 1.3666          | 0.1522   |
| 1.3226        | 4.92  | 32   | 1.3565          | 0.1522   |
| 1.3226        | 6.0   | 39   | 1.3902          | 0.1087   |
| 1.1987        | 6.92  | 45   | 1.3712          | 0.2174   |
| 1.1075        | 8.0   | 52   | 1.3197          | 0.3478   |
| 1.1075        | 8.92  | 58   | 1.3649          | 0.3696   |
| 0.9988        | 10.0  | 65   | 1.2583          | 0.3696   |
| 0.8863        | 10.92 | 71   | 1.2484          | 0.3696   |
| 0.8863        | 12.0  | 78   | 1.2869          | 0.4130   |
| 0.8228        | 12.92 | 84   | 1.1678          | 0.4783   |
| 0.7456        | 14.0  | 91   | 1.0275          | 0.6739   |
| 0.7456        | 14.92 | 97   | 0.9702          | 0.7174   |
| 0.6595        | 16.0  | 104  | 0.9103          | 0.6957   |
| 0.5995        | 16.92 | 110  | 0.8506          | 0.7391   |
| 0.5995        | 18.0  | 117  | 0.8514          | 0.7174   |
| 0.5826        | 18.92 | 123  | 0.8964          | 0.7391   |
| 0.4818        | 20.0  | 130  | 0.8550          | 0.7609   |
| 0.4818        | 20.92 | 136  | 0.7132          | 0.8261   |
| 0.4553        | 22.0  | 143  | 0.6973          | 0.7826   |
| 0.4553        | 22.92 | 149  | 0.7496          | 0.7391   |
| 0.4276        | 24.0  | 156  | 0.9087          | 0.6957   |
| 0.3375        | 24.92 | 162  | 0.7787          | 0.8261   |
| 0.3375        | 26.0  | 169  | 0.7132          | 0.8043   |
| 0.3199        | 26.92 | 175  | 0.7570          | 0.7391   |
| 0.2756        | 28.0  | 182  | 0.7873          | 0.6957   |
| 0.2756        | 28.92 | 188  | 0.7895          | 0.7609   |
| 0.2254        | 30.0  | 195  | 0.7443          | 0.8043   |
| 0.2576        | 30.92 | 201  | 0.9623          | 0.6739   |
| 0.2576        | 32.0  | 208  | 0.7349          | 0.7826   |
| 0.2113        | 32.92 | 214  | 0.7887          | 0.7609   |
| 0.1978        | 34.0  | 221  | 0.8921          | 0.7391   |
| 0.1978        | 34.92 | 227  | 0.8102          | 0.7391   |
| 0.2455        | 36.0  | 234  | 0.8947          | 0.7391   |
| 0.1809        | 36.92 | 240  | 0.8144          | 0.7826   |
| 0.1809        | 38.0  | 247  | 0.8290          | 0.7174   |
| 0.1967        | 38.92 | 253  | 0.8135          | 0.7391   |
| 0.1608        | 40.0  | 260  | 0.8065          | 0.7609   |
| 0.1608        | 40.92 | 266  | 0.7399          | 0.7609   |
| 0.1704        | 42.0  | 273  | 0.7099          | 0.8043   |
| 0.1704        | 42.92 | 279  | 0.7569          | 0.7826   |
| 0.1682        | 44.0  | 286  | 0.8459          | 0.7826   |
| 0.1607        | 44.92 | 292  | 0.7311          | 0.7609   |
| 0.1607        | 46.0  | 299  | 0.7833          | 0.7174   |
| 0.1589        | 46.92 | 305  | 0.8073          | 0.6957   |
| 0.1524        | 48.0  | 312  | 0.7473          | 0.7609   |
| 0.1524        | 48.92 | 318  | 0.6780          | 0.8043   |
| 0.1586        | 50.0  | 325  | 0.7573          | 0.7174   |
| 0.128         | 50.92 | 331  | 0.7614          | 0.7391   |
| 0.128         | 52.0  | 338  | 0.7338          | 0.7609   |
| 0.1254        | 52.92 | 344  | 0.7666          | 0.7391   |
| 0.1206        | 54.0  | 351  | 0.8433          | 0.7174   |
| 0.1206        | 54.92 | 357  | 0.8747          | 0.6957   |
| 0.1398        | 56.0  | 364  | 0.8940          | 0.7174   |
| 0.1536        | 56.92 | 370  | 0.7781          | 0.7826   |
| 0.1536        | 58.0  | 377  | 0.7351          | 0.7391   |
| 0.1281        | 58.92 | 383  | 0.7601          | 0.7174   |
| 0.1156        | 60.0  | 390  | 0.7991          | 0.7174   |
| 0.1156        | 60.92 | 396  | 0.7776          | 0.7609   |
| 0.0852        | 62.0  | 403  | 0.7838          | 0.7391   |
| 0.0852        | 62.92 | 409  | 0.7752          | 0.7609   |
| 0.1106        | 64.0  | 416  | 0.7541          | 0.7609   |
| 0.0817        | 64.92 | 422  | 0.7536          | 0.7391   |
| 0.0817        | 66.0  | 429  | 0.8129          | 0.7609   |
| 0.1211        | 66.92 | 435  | 0.7884          | 0.7609   |
| 0.0944        | 68.0  | 442  | 0.8011          | 0.7609   |
| 0.0944        | 68.92 | 448  | 0.8068          | 0.7391   |
| 0.1187        | 70.0  | 455  | 0.7796          | 0.7391   |
| 0.0935        | 70.92 | 461  | 0.7934          | 0.7391   |
| 0.0935        | 72.0  | 468  | 0.7367          | 0.7391   |
| 0.109         | 72.92 | 474  | 0.7515          | 0.7391   |
| 0.1006        | 73.85 | 480  | 0.7888          | 0.7174   |


### Framework versions

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