---
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: 0.78
---

<!-- 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: 0.4645
- Accuracy: 0.78

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.9231 | 3    | 0.5091          | 0.79     |
| No log        | 1.8462 | 6    | 0.6119          | 0.78     |
| No log        | 2.7692 | 9    | 0.5369          | 0.78     |
| 0.5446        | 4.0    | 13   | 0.4780          | 0.78     |
| 0.5446        | 4.9231 | 16   | 0.4721          | 0.78     |
| 0.5446        | 5.8462 | 19   | 0.4750          | 0.78     |
| 0.4041        | 6.7692 | 22   | 0.4746          | 0.78     |
| 0.4041        | 8.0    | 26   | 0.4700          | 0.78     |
| 0.4041        | 8.9231 | 29   | 0.4649          | 0.78     |
| 0.3755        | 9.2308 | 30   | 0.4645          | 0.78     |


### Framework versions

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