---
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-blank_img
  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: 0.9777131782945736
---

<!-- 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-blank_img

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: 0.0748
- Accuracy: 0.9777

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0898        | 0.99  | 72   | 0.1245          | 0.9428   |
| 0.152         | 1.99  | 145  | 0.0811          | 0.9748   |
| 0.1235        | 3.0   | 218  | 0.0958          | 0.9700   |
| 0.1065        | 4.0   | 291  | 0.0748          | 0.9777   |
| 0.1115        | 4.99  | 363  | 0.0947          | 0.9729   |
| 0.0804        | 5.99  | 436  | 0.0888          | 0.9758   |
| 0.0722        | 7.0   | 509  | 0.0827          | 0.9758   |
| 0.061         | 8.0   | 582  | 0.0899          | 0.9758   |
| 0.0706        | 8.99  | 654  | 0.0916          | 0.9758   |
| 0.0633        | 9.9   | 720  | 0.0937          | 0.9758   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0