---
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_six_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: 0.9512578616352201
---

<!-- 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_six_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: 0.1187
- Accuracy: 0.9513

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.619         | 0.94  | 11   | 1.1587          | 0.4984   |
| 0.841         | 1.96  | 23   | 0.5082          | 0.7689   |
| 0.4154        | 2.98  | 35   | 0.2849          | 0.8868   |
| 0.3476        | 4.0   | 47   | 0.2089          | 0.9418   |
| 0.2414        | 4.94  | 58   | 0.1575          | 0.9450   |
| 0.2128        | 5.96  | 70   | 0.1226          | 0.9497   |
| 0.1783        | 6.98  | 82   | 0.1203          | 0.9481   |
| 0.167         | 8.0   | 94   | 0.1169          | 0.9528   |
| 0.1723        | 8.94  | 105  | 0.1184          | 0.9513   |
| 0.1838        | 9.36  | 110  | 0.1187          | 0.9513   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2