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---

base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: SF-RHS-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: 0.822429906542056
---


<!-- 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-RHS-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: 0.5233
- Accuracy: 0.8224

## 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: 3e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.693         | 0.99  | 35   | 0.6927          | 0.6822   |
| 0.6919        | 2.0   | 71   | 0.6910          | 0.6916   |
| 0.6872        | 2.99  | 106  | 0.6821          | 0.6822   |
| 0.6613        | 4.0   | 142  | 0.6552          | 0.6542   |
| 0.6196        | 4.99  | 177  | 0.6403          | 0.6168   |
| 0.5695        | 6.0   | 213  | 0.6128          | 0.6449   |
| 0.5436        | 6.99  | 248  | 0.6765          | 0.5701   |
| 0.4836        | 8.0   | 284  | 0.6075          | 0.6542   |
| 0.4902        | 8.99  | 319  | 0.5788          | 0.6355   |
| 0.4759        | 10.0  | 355  | 0.5284          | 0.7196   |
| 0.4746        | 10.99 | 390  | 0.5532          | 0.6822   |
| 0.4067        | 12.0  | 426  | 0.5356          | 0.7383   |
| 0.4138        | 12.99 | 461  | 0.5042          | 0.7477   |
| 0.3752        | 14.0  | 497  | 0.5063          | 0.7383   |
| 0.4158        | 14.99 | 532  | 0.4952          | 0.7570   |
| 0.3646        | 16.0  | 568  | 0.5440          | 0.7383   |
| 0.3644        | 16.99 | 603  | 0.5146          | 0.7757   |
| 0.3411        | 18.0  | 639  | 0.5208          | 0.7757   |
| 0.3052        | 18.99 | 674  | 0.5785          | 0.7383   |
| 0.3398        | 20.0  | 710  | 0.5366          | 0.7383   |
| 0.3103        | 20.99 | 745  | 0.5751          | 0.7290   |
| 0.3168        | 22.0  | 781  | 0.5194          | 0.7664   |
| 0.2927        | 22.99 | 816  | 0.5008          | 0.7944   |
| 0.2874        | 24.0  | 852  | 0.5216          | 0.7944   |
| 0.3021        | 24.99 | 887  | 0.5695          | 0.7570   |
| 0.2978        | 26.0  | 923  | 0.5643          | 0.7570   |
| 0.2743        | 26.99 | 958  | 0.5767          | 0.7570   |
| 0.2753        | 28.0  | 994  | 0.5125          | 0.7664   |
| 0.2773        | 28.99 | 1029 | 0.5246          | 0.7664   |
| 0.2775        | 30.0  | 1065 | 0.5473          | 0.7850   |
| 0.268         | 30.99 | 1100 | 0.5286          | 0.7664   |
| 0.2586        | 32.0  | 1136 | 0.5233          | 0.7850   |
| 0.2458        | 32.99 | 1171 | 0.5451          | 0.7757   |
| 0.2524        | 34.0  | 1207 | 0.5268          | 0.7850   |
| 0.2438        | 34.99 | 1242 | 0.5228          | 0.7757   |
| 0.2429        | 36.0  | 1278 | 0.5391          | 0.7664   |
| 0.2689        | 36.99 | 1313 | 0.5237          | 0.7850   |
| 0.2362        | 38.0  | 1349 | 0.5561          | 0.7664   |
| 0.2656        | 38.99 | 1384 | 0.5233          | 0.8224   |
| 0.264         | 39.44 | 1400 | 0.5112          | 0.8037   |


### Framework versions

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