---
library_name: transformers
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-RD-da-colab
  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: 0.5018181818181818
---

<!-- 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-RD-da-colab

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: 5.5780
- Accuracy: 0.5018

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5414        | 1.0   | 96   | 9.3183          | 0.4945   |
| 0.533         | 2.0   | 192  | 7.8263          | 0.5      |
| 0.3449        | 3.0   | 288  | 8.6048          | 0.4945   |
| 0.3157        | 4.0   | 384  | 8.4227          | 0.4945   |
| 0.2686        | 5.0   | 480  | 4.3190          | 0.5473   |
| 0.2987        | 6.0   | 576  | 5.0817          | 0.5164   |
| 0.3415        | 7.0   | 672  | 5.2399          | 0.5127   |
| 0.2396        | 8.0   | 768  | 6.7857          | 0.5018   |
| 0.2618        | 9.0   | 864  | 6.5777          | 0.5055   |
| 0.297         | 10.0  | 960  | 6.6086          | 0.5036   |
| 0.2413        | 11.0  | 1056 | 3.6891          | 0.5236   |
| 0.2074        | 12.0  | 1152 | 6.8991          | 0.5      |
| 0.2029        | 13.0  | 1248 | 5.8597          | 0.5018   |
| 0.2353        | 14.0  | 1344 | 7.3848          | 0.5036   |
| 0.1748        | 15.0  | 1440 | 4.9503          | 0.5109   |
| 0.1885        | 16.0  | 1536 | 7.2151          | 0.4982   |
| 0.1967        | 17.0  | 1632 | 7.9847          | 0.4982   |
| 0.1881        | 18.0  | 1728 | 4.5008          | 0.5109   |
| 0.172         | 19.0  | 1824 | 4.7565          | 0.5273   |
| 0.2222        | 20.0  | 1920 | 6.2814          | 0.4964   |
| 0.1673        | 21.0  | 2016 | 8.1814          | 0.4964   |
| 0.1831        | 22.0  | 2112 | 4.4184          | 0.5164   |
| 0.1121        | 23.0  | 2208 | 6.0737          | 0.4982   |
| 0.1464        | 24.0  | 2304 | 5.3006          | 0.5018   |
| 0.1343        | 25.0  | 2400 | 5.6166          | 0.5036   |
| 0.1385        | 26.0  | 2496 | 6.1437          | 0.5018   |
| 0.1153        | 27.0  | 2592 | 6.3232          | 0.5018   |
| 0.1175        | 28.0  | 2688 | 6.2047          | 0.5036   |
| 0.1107        | 29.0  | 2784 | 7.5461          | 0.4982   |
| 0.0914        | 30.0  | 2880 | 7.4573          | 0.4982   |
| 0.1123        | 31.0  | 2976 | 6.2770          | 0.4982   |
| 0.1268        | 32.0  | 3072 | 5.1979          | 0.5073   |
| 0.1074        | 33.0  | 3168 | 4.9253          | 0.5036   |
| 0.0712        | 34.0  | 3264 | 5.0555          | 0.5018   |
| 0.0792        | 35.0  | 3360 | 6.1480          | 0.4982   |
| 0.1097        | 36.0  | 3456 | 6.5916          | 0.4982   |
| 0.1035        | 37.0  | 3552 | 7.4887          | 0.4982   |
| 0.1066        | 38.0  | 3648 | 6.1041          | 0.5      |
| 0.0887        | 39.0  | 3744 | 6.7739          | 0.4982   |
| 0.0889        | 40.0  | 3840 | 5.5780          | 0.5018   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3