---
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-finetuned-student_two_classes
  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: 0.8
---

<!-- 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-finetuned-student_two_classes

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: 0.6649
- Accuracy: 0.8

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3416        | 1.0   | 13   | 0.6767          | 0.81     |
| 0.2745        | 2.0   | 26   | 0.7166          | 0.81     |
| 0.2482        | 3.0   | 39   | 0.7644          | 0.83     |
| 0.2664        | 4.0   | 52   | 0.7142          | 0.81     |
| 0.2372        | 5.0   | 65   | 0.8010          | 0.85     |
| 0.2238        | 6.0   | 78   | 0.8655          | 0.86     |
| 0.1687        | 7.0   | 91   | 0.8156          | 0.83     |
| 0.209         | 8.0   | 104  | 0.8460          | 0.83     |
| 0.4251        | 9.0   | 117  | 0.7301          | 0.81     |
| 0.4392        | 10.0  | 130  | 0.6775          | 0.78     |
| 0.3285        | 11.0  | 143  | 0.7145          | 0.81     |
| 0.3178        | 12.0  | 156  | 0.7431          | 0.83     |
| 0.4715        | 13.0  | 169  | 0.6973          | 0.81     |
| 0.373         | 14.0  | 182  | 0.6912          | 0.81     |
| 0.3378        | 15.0  | 195  | 0.7018          | 0.82     |
| 0.3867        | 16.0  | 208  | 0.6885          | 0.81     |
| 0.3525        | 17.0  | 221  | 0.6761          | 0.81     |
| 0.4253        | 18.0  | 234  | 0.6643          | 0.8      |
| 0.325         | 19.0  | 247  | 0.6643          | 0.8      |
| 0.372         | 20.0  | 260  | 0.6649          | 0.8      |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1