---
license: apache-2.0
base_model: mansee/swin-tiny-patch4-window7-224-img_orientation
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: 0.7794067507671326
---

<!-- 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 [mansee/swin-tiny-patch4-window7-224-img_orientation](https://huggingface.co/mansee/swin-tiny-patch4-window7-224-img_orientation) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4538
- Accuracy: 0.7794

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3217        | 1.0   | 412  | 0.4922          | 0.7533   |
| 0.3716        | 2.0   | 825  | 0.4986          | 0.7601   |
| 0.3756        | 3.0   | 1237 | 0.4427          | 0.7762   |
| 0.3926        | 4.0   | 1650 | 0.4515          | 0.7733   |
| 0.3859        | 5.0   | 2062 | 0.4394          | 0.7717   |
| 0.3822        | 6.0   | 2475 | 0.4410          | 0.7784   |
| 0.3804        | 7.0   | 2887 | 0.4561          | 0.7767   |
| 0.3231        | 8.0   | 3300 | 0.4505          | 0.7784   |
| 0.3295        | 9.0   | 3712 | 0.4607          | 0.7789   |
| 0.321         | 9.99  | 4120 | 0.4538          | 0.7794   |


### Framework versions

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