---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-DMAE
  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: 0.10869565217391304
---

<!-- 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-DMAE

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: 113.8668
- Accuracy: 0.1087

## 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: 2.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.86  | 3    | 113.8668        | 0.1087   |
| No log        | 2.0   | 7    | 113.8652        | 0.1087   |
| 114.139       | 2.86  | 10   | 113.8636        | 0.1087   |
| 114.139       | 4.0   | 14   | 113.8630        | 0.1087   |
| 114.139       | 4.86  | 17   | 113.8617        | 0.1087   |
| 113.4957      | 6.0   | 21   | 113.8592        | 0.1087   |
| 113.4957      | 6.86  | 24   | 113.8579        | 0.1087   |
| 113.4957      | 8.0   | 28   | 113.8578        | 0.1087   |
| 111.7345      | 8.86  | 31   | 113.8550        | 0.1087   |
| 111.7345      | 10.0  | 35   | 113.8531        | 0.1087   |
| 111.7345      | 10.86 | 38   | 113.8520        | 0.1087   |
| 115.9214      | 12.0  | 42   | 113.8497        | 0.1087   |
| 115.9214      | 12.86 | 45   | 113.8484        | 0.1087   |
| 115.9214      | 14.0  | 49   | 113.8455        | 0.1087   |
| 112.3215      | 14.86 | 52   | 113.8392        | 0.1087   |
| 112.3215      | 16.0  | 56   | 113.8351        | 0.1087   |
| 112.3215      | 16.86 | 59   | 113.8354        | 0.1087   |
| 113.1908      | 18.0  | 63   | 113.8316        | 0.1087   |
| 113.1908      | 18.86 | 66   | 113.8295        | 0.1087   |
| 114.062       | 20.0  | 70   | 113.8284        | 0.1087   |
| 114.062       | 20.86 | 73   | 113.8253        | 0.1087   |
| 114.062       | 22.0  | 77   | 113.8235        | 0.1087   |
| 114.5312      | 22.86 | 80   | 113.8207        | 0.1087   |
| 114.5312      | 24.0  | 84   | 113.8126        | 0.1087   |
| 114.5312      | 24.86 | 87   | 113.8100        | 0.1087   |
| 114.5216      | 26.0  | 91   | 113.8053        | 0.1087   |
| 114.5216      | 26.86 | 94   | 113.8032        | 0.1087   |
| 114.5216      | 28.0  | 98   | 113.8035        | 0.1087   |
| 112.7612      | 28.86 | 101  | 113.7992        | 0.1087   |
| 112.7612      | 30.0  | 105  | 113.7939        | 0.1087   |
| 112.7612      | 30.86 | 108  | 113.7967        | 0.1087   |
| 114.2748      | 32.0  | 112  | 113.7973        | 0.1087   |
| 114.2748      | 32.86 | 115  | 113.7971        | 0.1087   |
| 114.2748      | 34.0  | 119  | 113.7908        | 0.1087   |
| 114.0708      | 34.29 | 120  | 113.7932        | 0.1087   |


### Framework versions

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