---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-img_orientation
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7280604310153299
---

<!-- 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. -->

# swin-tiny-patch4-window7-224-img_orientation

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4743
- Accuracy: 0.7281

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6659        | 1.0   | 316  | 0.5536          | 0.6850   |
| 0.5971        | 2.0   | 633  | 0.4986          | 0.7170   |
| 0.5782        | 3.0   | 949  | 0.4825          | 0.7172   |
| 0.5428        | 4.0   | 1266 | 0.4664          | 0.7141   |
| 0.5131        | 5.0   | 1582 | 0.4785          | 0.7150   |
| 0.4851        | 6.0   | 1899 | 0.4706          | 0.7225   |
| 0.4457        | 7.0   | 2215 | 0.4729          | 0.7187   |
| 0.4407        | 8.0   | 2532 | 0.4759          | 0.7207   |
| 0.4636        | 9.0   | 2848 | 0.4732          | 0.7250   |
| 0.4212        | 9.98  | 3160 | 0.4743          | 0.7281   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3