---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: SF-DMAE-DA
  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: 0.8260869565217391
---

<!-- 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. -->

# SF-DMAE-DA

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: 0.8371
- Accuracy: 0.8261

## 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: 0.15
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3856        | 0.96  | 11   | 1.3864          | 0.1304   |
| 1.376         | 2.0   | 23   | 1.3770          | 0.1522   |
| 1.3201        | 2.96  | 34   | 1.3578          | 0.2609   |
| 1.2272        | 4.0   | 46   | 1.3456          | 0.2174   |
| 1.0812        | 4.96  | 57   | 1.3423          | 0.4348   |
| 1.0301        | 6.0   | 69   | 1.2316          | 0.4130   |
| 0.8375        | 6.96  | 80   | 1.1414          | 0.5      |
| 0.806         | 8.0   | 92   | 1.1792          | 0.4348   |
| 0.6895        | 8.96  | 103  | 1.0475          | 0.5      |
| 0.6142        | 10.0  | 115  | 0.9662          | 0.6522   |
| 0.5602        | 10.96 | 126  | 1.0034          | 0.6739   |
| 0.6118        | 12.0  | 138  | 0.9099          | 0.6087   |
| 0.56          | 12.96 | 149  | 0.9165          | 0.7609   |
| 0.4118        | 14.0  | 161  | 0.8947          | 0.7826   |
| 0.4115        | 14.96 | 172  | 0.9526          | 0.7391   |
| 0.4596        | 16.0  | 184  | 1.0376          | 0.6957   |
| 0.4066        | 16.96 | 195  | 0.8371          | 0.8261   |
| 0.3437        | 18.0  | 207  | 0.9002          | 0.8043   |
| 0.3279        | 18.96 | 218  | 0.8110          | 0.8043   |
| 0.3039        | 20.0  | 230  | 0.6589          | 0.8043   |
| 0.2315        | 20.96 | 241  | 0.8245          | 0.8261   |
| 0.2588        | 22.0  | 253  | 0.8610          | 0.7826   |
| 0.1889        | 22.96 | 264  | 0.7608          | 0.8043   |
| 0.2326        | 24.0  | 276  | 0.8180          | 0.8261   |
| 0.2107        | 24.96 | 287  | 0.8907          | 0.8261   |
| 0.1917        | 26.0  | 299  | 0.8404          | 0.7826   |
| 0.2           | 26.96 | 310  | 0.8136          | 0.7826   |
| 0.194         | 28.0  | 322  | 0.8591          | 0.7609   |
| 0.21          | 28.96 | 333  | 0.8823          | 0.8261   |
| 0.1917        | 30.0  | 345  | 0.7817          | 0.7609   |
| 0.1342        | 30.96 | 356  | 0.8810          | 0.8043   |
| 0.1185        | 32.0  | 368  | 0.9961          | 0.8043   |
| 0.1805        | 32.96 | 379  | 0.9183          | 0.8043   |
| 0.1548        | 34.0  | 391  | 0.9017          | 0.8261   |
| 0.1276        | 34.96 | 402  | 0.9056          | 0.8043   |
| 0.186         | 36.0  | 414  | 0.9376          | 0.8043   |
| 0.135         | 36.96 | 425  | 0.9160          | 0.8043   |
| 0.1313        | 38.0  | 437  | 0.8822          | 0.8043   |
| 0.1628        | 38.26 | 440  | 0.8337          | 0.8261   |


### Framework versions

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