---
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: 0.43478260869565216
---

<!-- 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: 1.2103
- Accuracy: 0.4348

## 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: 0.05
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.86  | 3    | 113.8089        | 0.1087   |
| No log        | 2.0   | 7    | 719662.6875     | 0.1087   |
| 113.1437      | 2.86  | 10   | 3930.8594       | 0.1087   |
| 113.1437      | 4.0   | 14   | 57703.1484      | 0.1087   |
| 113.1437      | 4.86  | 17   | 1127.0548       | 0.3261   |
| 96.1157       | 6.0   | 21   | 131.2882        | 0.1087   |
| 96.1157       | 6.86  | 24   | 305.9370        | 0.0870   |
| 96.1157       | 8.0   | 28   | 209.0138        | 0.1087   |
| 38.8121       | 8.86  | 31   | 30.6911         | 0.1304   |
| 38.8121       | 10.0  | 35   | 7.7503          | 0.4565   |
| 38.8121       | 10.86 | 38   | 16.1361         | 0.3261   |
| 10.6492       | 12.0  | 42   | 7.8875          | 0.4565   |
| 10.6492       | 12.86 | 45   | 4.8321          | 0.4565   |
| 10.6492       | 14.0  | 49   | 8.2543          | 0.4565   |
| 3.6688        | 14.86 | 52   | 3.3603          | 0.4565   |
| 3.6688        | 16.0  | 56   | 3.9023          | 0.4565   |
| 3.6688        | 16.86 | 59   | 3.6221          | 0.4565   |
| 1.5847        | 18.0  | 63   | 3.2802          | 0.4565   |
| 1.5847        | 18.86 | 66   | 1.8639          | 0.4565   |
| 1.5235        | 20.0  | 70   | 2.5394          | 0.4565   |
| 1.5235        | 20.86 | 73   | 1.4062          | 0.4783   |
| 1.5235        | 22.0  | 77   | 1.4145          | 0.3913   |
| 1.3634        | 22.86 | 80   | 1.3275          | 0.4565   |
| 1.3634        | 24.0  | 84   | 1.3357          | 0.3478   |
| 1.3634        | 24.86 | 87   | 1.4708          | 0.4565   |
| 1.2807        | 26.0  | 91   | 1.2909          | 0.4565   |
| 1.2807        | 26.86 | 94   | 1.3445          | 0.4565   |
| 1.2807        | 28.0  | 98   | 1.2974          | 0.3696   |
| 1.2625        | 28.86 | 101  | 1.3482          | 0.4565   |
| 1.2625        | 30.0  | 105  | 1.2866          | 0.3478   |
| 1.2625        | 30.86 | 108  | 1.2364          | 0.4783   |
| 1.2472        | 32.0  | 112  | 1.2389          | 0.4130   |
| 1.2472        | 32.86 | 115  | 1.2459          | 0.3478   |
| 1.2472        | 34.0  | 119  | 1.2090          | 0.4348   |
| 1.2117        | 34.29 | 120  | 1.2103          | 0.4348   |


### Framework versions

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