---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-bottom_cleaned_data-hpt
  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: 0.9694041867954911
---

<!-- 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-bottom_cleaned_data-hpt

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: 0.0701
- Accuracy: 0.9694

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4307        | 0.99  | 99   | 0.2332          | 0.9227   |
| 0.3425        | 2.0   | 199  | 0.1904          | 0.9404   |
| 0.29          | 3.0   | 299  | 0.1316          | 0.9388   |
| 0.2597        | 3.99  | 398  | 0.1158          | 0.9533   |
| 0.2638        | 4.99  | 498  | 0.0987          | 0.9614   |
| 0.209         | 6.0   | 598  | 0.0802          | 0.9710   |
| 0.1776        | 7.0   | 698  | 0.0838          | 0.9597   |
| 0.1776        | 7.99  | 797  | 0.0787          | 0.9694   |
| 0.1502        | 9.0   | 897  | 0.0797          | 0.9726   |
| 0.1402        | 9.93  | 990  | 0.0701          | 0.9694   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3