---
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-sealv1
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9793103448275862
---

<!-- 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-sealv1

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: 0.0650
- Accuracy: 0.9793

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.95  | 5    | 1.2920          | 0.4966   |
| 1.1379        | 1.9   | 10   | 1.0177          | 0.4966   |
| 1.1379        | 2.86  | 15   | 0.7626          | 0.8759   |
| 0.6784        | 4.0   | 21   | 0.5388          | 0.9310   |
| 0.6784        | 4.95  | 26   | 0.4191          | 0.9103   |
| 0.3269        | 5.9   | 31   | 0.3990          | 0.8897   |
| 0.3269        | 6.86  | 36   | 0.2090          | 0.9517   |
| 0.2068        | 8.0   | 42   | 0.1819          | 0.9586   |
| 0.2068        | 8.95  | 47   | 0.1192          | 0.9655   |
| 0.1104        | 9.9   | 52   | 0.0682          | 0.9724   |
| 0.1104        | 10.86 | 57   | 0.0854          | 0.9724   |
| 0.0571        | 12.0  | 63   | 0.0816          | 0.9655   |
| 0.0571        | 12.95 | 68   | 0.0535          | 0.9793   |
| 0.0382        | 13.9  | 73   | 0.0491          | 0.9793   |
| 0.0382        | 14.86 | 78   | 0.0534          | 0.9793   |
| 0.0158        | 16.0  | 84   | 0.0369          | 0.9793   |
| 0.0158        | 16.95 | 89   | 0.1111          | 0.9724   |
| 0.0082        | 17.9  | 94   | 0.0515          | 0.9862   |
| 0.0082        | 18.86 | 99   | 0.0713          | 0.9793   |
| 0.0105        | 20.0  | 105  | 0.0598          | 0.9793   |
| 0.009         | 20.95 | 110  | 0.0759          | 0.9724   |
| 0.009         | 21.9  | 115  | 0.0769          | 0.9793   |
| 0.0134        | 22.86 | 120  | 0.0702          | 0.9793   |
| 0.0134        | 24.0  | 126  | 0.0605          | 0.9793   |
| 0.0042        | 24.95 | 131  | 0.0621          | 0.9793   |
| 0.0042        | 25.9  | 136  | 0.0654          | 0.9793   |
| 0.0027        | 26.86 | 141  | 0.0666          | 0.9724   |
| 0.0027        | 28.0  | 147  | 0.0665          | 0.9793   |
| 0.0065        | 28.57 | 150  | 0.0650          | 0.9793   |


### Framework versions

- Transformers 4.38.2
- Pytorch 1.10.2+cu113
- Datasets 2.18.0
- Tokenizers 0.15.2