---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-uploads-classifier-v2
  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: 0.984313725490196
---

<!-- 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-uploads-classifier-v2

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: 0.0745
- Accuracy: 0.9843

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2482        | 1.0   | 18   | 0.4781          | 0.8824   |
| 0.3036        | 2.0   | 36   | 0.0936          | 0.9804   |
| 0.1687        | 3.0   | 54   | 0.0745          | 0.9843   |
| 0.1392        | 4.0   | 72   | 0.0980          | 0.9725   |
| 0.14          | 5.0   | 90   | 0.0778          | 0.9765   |
| 0.1186        | 6.0   | 108  | 0.0837          | 0.9725   |
| 0.1088        | 7.0   | 126  | 0.0645          | 0.9804   |
| 0.0789        | 8.0   | 144  | 0.0675          | 0.9765   |
| 0.0644        | 9.0   | 162  | 0.0940          | 0.9686   |
| 0.0582        | 10.0  | 180  | 0.0879          | 0.9725   |
| 0.0591        | 11.0  | 198  | 0.0935          | 0.9686   |
| 0.0538        | 12.0  | 216  | 0.0540          | 0.9804   |
| 0.0588        | 13.0  | 234  | 0.0725          | 0.9686   |
| 0.0538        | 14.0  | 252  | 0.0637          | 0.9765   |
| 0.0462        | 15.0  | 270  | 0.0694          | 0.9725   |
| 0.0352        | 16.0  | 288  | 0.0771          | 0.9686   |
| 0.0536        | 17.0  | 306  | 0.0629          | 0.9804   |
| 0.0403        | 18.0  | 324  | 0.0933          | 0.9686   |
| 0.0412        | 19.0  | 342  | 0.0848          | 0.9725   |
| 0.0305        | 20.0  | 360  | 0.0820          | 0.9725   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3