---
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swiftformer-xs-OT
  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: 0.8548387096774194
---

<!-- 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-OT

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: 0.4956
- Accuracy: 0.8548

## 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: 0.0015
- 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        | 0.89  | 4    | 1.3804          | 0.5161   |
| No log        | 2.0   | 9    | 1.2554          | 0.5323   |
| 1.3469        | 2.89  | 13   | 0.9725          | 0.6613   |
| 1.3469        | 4.0   | 18   | 0.7086          | 0.7581   |
| 0.9831        | 4.89  | 22   | 0.8856          | 0.7258   |
| 0.9831        | 6.0   | 27   | 0.7724          | 0.7581   |
| 0.7441        | 6.89  | 31   | 0.8190          | 0.7258   |
| 0.7441        | 8.0   | 36   | 0.6897          | 0.7742   |
| 0.6939        | 8.89  | 40   | 0.6599          | 0.7258   |
| 0.6939        | 10.0  | 45   | 0.6288          | 0.7742   |
| 0.6939        | 10.89 | 49   | 0.6333          | 0.7581   |
| 0.5861        | 12.0  | 54   | 0.6206          | 0.7742   |
| 0.5861        | 12.89 | 58   | 0.5263          | 0.7903   |
| 0.5018        | 14.0  | 63   | 0.5836          | 0.8065   |
| 0.5018        | 14.89 | 67   | 0.6125          | 0.7419   |
| 0.4642        | 16.0  | 72   | 0.5431          | 0.8065   |
| 0.4642        | 16.89 | 76   | 0.5893          | 0.8387   |
| 0.4064        | 18.0  | 81   | 0.4997          | 0.8065   |
| 0.4064        | 18.89 | 85   | 0.5474          | 0.7742   |
| 0.4275        | 20.0  | 90   | 0.6748          | 0.7903   |
| 0.4275        | 20.89 | 94   | 0.6369          | 0.7581   |
| 0.4275        | 22.0  | 99   | 0.5610          | 0.7742   |
| 0.373         | 22.89 | 103  | 0.5260          | 0.7903   |
| 0.373         | 24.0  | 108  | 0.5416          | 0.8387   |
| 0.2931        | 24.89 | 112  | 0.5146          | 0.8387   |
| 0.2931        | 26.0  | 117  | 0.5180          | 0.7742   |
| 0.3135        | 26.89 | 121  | 0.5169          | 0.8226   |
| 0.3135        | 28.0  | 126  | 0.5491          | 0.8387   |
| 0.2342        | 28.89 | 130  | 0.5385          | 0.8387   |
| 0.2342        | 30.0  | 135  | 0.5456          | 0.8387   |
| 0.2342        | 30.89 | 139  | 0.4956          | 0.8548   |
| 0.2411        | 32.0  | 144  | 0.5254          | 0.8226   |
| 0.2411        | 32.89 | 148  | 0.5533          | 0.8387   |
| 0.2135        | 34.0  | 153  | 0.5613          | 0.8387   |
| 0.2135        | 34.89 | 157  | 0.5748          | 0.8226   |
| 0.1904        | 35.56 | 160  | 0.5844          | 0.8387   |


### Framework versions

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