---
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-wuhan
  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: 1.0
---

<!-- 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-wuhan

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: 0.0000
- Accuracy: 1.0

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 3    | 0.6245          | 0.7778   |
| No log        | 2.0   | 6    | 0.5321          | 0.7778   |
| No log        | 3.0   | 9    | 0.5123          | 0.7778   |
| 0.6482        | 4.0   | 12   | 0.4956          | 0.7778   |
| 0.6482        | 5.0   | 15   | 0.4585          | 0.7778   |
| 0.6482        | 6.0   | 18   | 0.3743          | 0.8611   |
| 0.5574        | 7.0   | 21   | 0.2842          | 0.9167   |
| 0.5574        | 8.0   | 24   | 0.2125          | 0.9167   |
| 0.5574        | 9.0   | 27   | 0.2683          | 0.9167   |
| 0.4882        | 10.0  | 30   | 0.1316          | 0.9444   |
| 0.4882        | 11.0  | 33   | 0.1366          | 0.9444   |
| 0.4882        | 12.0  | 36   | 0.0745          | 0.9722   |
| 0.4882        | 13.0  | 39   | 0.1065          | 0.9444   |
| 0.0907        | 14.0  | 42   | 0.0477          | 0.9722   |
| 0.0907        | 15.0  | 45   | 0.0460          | 0.9444   |
| 0.0907        | 16.0  | 48   | 0.0438          | 0.9722   |
| 0.0481        | 17.0  | 51   | 0.0203          | 1.0      |
| 0.0481        | 18.0  | 54   | 0.0093          | 1.0      |
| 0.0481        | 19.0  | 57   | 0.0082          | 1.0      |
| 0.013         | 20.0  | 60   | 0.0017          | 1.0      |
| 0.013         | 21.0  | 63   | 0.0008          | 1.0      |
| 0.013         | 22.0  | 66   | 0.0002          | 1.0      |
| 0.013         | 23.0  | 69   | 0.0001          | 1.0      |
| 0.0101        | 24.0  | 72   | 0.0938          | 0.9722   |
| 0.0101        | 25.0  | 75   | 0.1019          | 0.9722   |
| 0.0101        | 26.0  | 78   | 0.0005          | 1.0      |
| 0.0085        | 27.0  | 81   | 0.0000          | 1.0      |
| 0.0085        | 28.0  | 84   | 0.0000          | 1.0      |
| 0.0085        | 29.0  | 87   | 0.0001          | 1.0      |
| 0.0196        | 30.0  | 90   | 0.0001          | 1.0      |
| 0.0196        | 31.0  | 93   | 0.0001          | 1.0      |
| 0.0196        | 32.0  | 96   | 0.0000          | 1.0      |
| 0.0196        | 33.0  | 99   | 0.0000          | 1.0      |
| 0.0027        | 34.0  | 102  | 0.0000          | 1.0      |
| 0.0027        | 35.0  | 105  | 0.0000          | 1.0      |
| 0.0027        | 36.0  | 108  | 0.0000          | 1.0      |
| 0.0016        | 37.0  | 111  | 0.0000          | 1.0      |
| 0.0016        | 38.0  | 114  | 0.0000          | 1.0      |
| 0.0016        | 39.0  | 117  | 0.0000          | 1.0      |
| 0.0021        | 40.0  | 120  | 0.0000          | 1.0      |
| 0.0021        | 41.0  | 123  | 0.0000          | 1.0      |
| 0.0021        | 42.0  | 126  | 0.0000          | 1.0      |
| 0.0021        | 43.0  | 129  | 0.0000          | 1.0      |
| 0.0024        | 44.0  | 132  | 0.0000          | 1.0      |
| 0.0024        | 45.0  | 135  | 0.0000          | 1.0      |
| 0.0024        | 46.0  | 138  | 0.0000          | 1.0      |
| 0.0009        | 47.0  | 141  | 0.0000          | 1.0      |
| 0.0009        | 48.0  | 144  | 0.0000          | 1.0      |
| 0.0009        | 49.0  | 147  | 0.0000          | 1.0      |
| 0.0006        | 50.0  | 150  | 0.0000          | 1.0      |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.1
- Tokenizers 0.13.3