---
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: 113.9563
- 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: 0.00015
- 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    | 113.9563        | 0.1087   |
| No log        | 2.0   | 7    | 113.9524        | 0.1087   |
| 114.2271      | 2.86  | 10   | 113.9454        | 0.1087   |
| 114.2271      | 4.0   | 14   | 113.9389        | 0.1087   |
| 114.2271      | 4.86  | 17   | 113.9226        | 0.1087   |
| 113.5566      | 6.0   | 21   | 113.8982        | 0.1087   |
| 113.5566      | 6.86  | 24   | 113.8425        | 0.1087   |
| 113.5566      | 8.0   | 28   | 113.7478        | 0.1087   |
| 111.6907      | 8.86  | 31   | 113.6538        | 0.1087   |
| 111.6907      | 10.0  | 35   | 113.5589        | 0.1087   |
| 111.6907      | 10.86 | 38   | 113.5002        | 0.1087   |
| 115.67        | 12.0  | 42   | 113.4496        | 0.1087   |
| 115.67        | 12.86 | 45   | 113.3752        | 0.1087   |
| 115.67        | 14.0  | 49   | 113.2129        | 0.1087   |
| 111.8054      | 14.86 | 52   | 113.0828        | 0.1087   |
| 111.8054      | 16.0  | 56   | 112.8805        | 0.1087   |
| 111.8054      | 16.86 | 59   | 112.9013        | 0.1087   |
| 112.3831      | 18.0  | 63   | 112.8123        | 0.1087   |
| 112.3831      | 18.86 | 66   | 113.0190        | 0.1087   |
| 113.1097      | 20.0  | 70   | 113.2929        | 0.1087   |
| 113.1097      | 20.86 | 73   | 112.8861        | 0.1087   |
| 113.1097      | 22.0  | 77   | 112.7154        | 0.1087   |
| 113.3674      | 22.86 | 80   | 112.6943        | 0.1087   |
| 113.3674      | 24.0  | 84   | 112.3937        | 0.1087   |
| 113.3674      | 24.86 | 87   | 112.3862        | 0.1087   |
| 113.1472      | 26.0  | 91   | 112.2693        | 0.1087   |
| 113.1472      | 26.86 | 94   | 112.3107        | 0.1087   |
| 113.1472      | 28.0  | 98   | 112.4216        | 0.1087   |
| 111.3252      | 28.86 | 101  | 112.3318        | 0.1087   |
| 111.3252      | 30.0  | 105  | 112.3517        | 0.1087   |
| 111.3252      | 30.86 | 108  | 112.4213        | 0.1087   |
| 112.827       | 32.0  | 112  | 112.4838        | 0.1087   |
| 112.827       | 32.86 | 115  | 112.4490        | 0.1087   |
| 112.827       | 34.0  | 119  | 112.1525        | 0.1087   |
| 112.5631      | 34.29 | 120  | 112.1956        | 0.1087   |


### Framework versions

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