---
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: 113.8184
- 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: 0.0003
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.86  | 3    | 113.8184        | 0.1087   |
| No log        | 2.0   | 7    | 113.8094        | 0.1087   |
| 114.0867      | 2.86  | 10   | 113.7944        | 0.1087   |
| 114.0867      | 4.0   | 14   | 113.7881        | 0.1087   |
| 114.0867      | 4.86  | 17   | 113.7100        | 0.1087   |
| 113.3425      | 6.0   | 21   | 113.5884        | 0.1087   |
| 113.3425      | 6.86  | 24   | 113.4998        | 0.1087   |
| 113.3425      | 8.0   | 28   | 113.0578        | 0.1087   |
| 111.228       | 8.86  | 31   | 112.8053        | 0.1087   |
| 111.228       | 10.0  | 35   | 112.5202        | 0.1087   |
| 111.228       | 10.86 | 38   | 112.5811        | 0.1087   |
| 114.9647      | 12.0  | 42   | 112.6090        | 0.1087   |
| 114.9647      | 12.86 | 45   | 112.4973        | 0.1087   |
| 114.9647      | 14.0  | 49   | 111.9761        | 0.1087   |
| 110.7738      | 14.86 | 52   | 111.8117        | 0.1087   |
| 110.7738      | 16.0  | 56   | 111.6589        | 0.1087   |
| 110.7738      | 16.86 | 59   | 111.5367        | 0.1087   |
| 111.0505      | 18.0  | 63   | 111.7016        | 0.1087   |
| 111.0505      | 18.86 | 66   | 111.9068        | 0.1087   |
| 111.4545      | 20.0  | 70   | 111.6203        | 0.1087   |
| 111.4545      | 20.86 | 73   | 111.1266        | 0.1087   |
| 111.4545      | 22.0  | 77   | 110.2879        | 0.1087   |
| 111.2779      | 22.86 | 80   | 109.8523        | 0.1087   |
| 111.2779      | 24.0  | 84   | 109.5283        | 0.1087   |
| 111.2779      | 24.86 | 87   | 109.9590        | 0.1087   |
| 110.5166      | 26.0  | 91   | 109.9752        | 0.1087   |
| 110.5166      | 26.86 | 94   | 109.5435        | 0.1087   |
| 110.5166      | 28.0  | 98   | 109.5712        | 0.1087   |
| 108.66        | 28.86 | 101  | 108.8924        | 0.1087   |
| 108.66        | 30.0  | 105  | 108.3990        | 0.1087   |
| 108.66        | 30.86 | 108  | 108.7050        | 0.1087   |
| 109.688       | 32.0  | 112  | 108.7237        | 0.1087   |
| 109.688       | 32.86 | 115  | 109.0679        | 0.1087   |
| 109.688       | 34.0  | 119  | 108.5750        | 0.1087   |
| 109.4549      | 34.29 | 120  | 108.5167        | 0.1087   |


### Framework versions

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