---
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: 0.9119804400977995
---

<!-- 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: 0.2553
- Accuracy: 0.9120

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1068        | 0.95  | 14   | 0.6518          | 0.7066   |
| 0.4912        | 1.97  | 29   | 0.4668          | 0.8435   |
| 0.2749        | 2.98  | 44   | 0.4127          | 0.8704   |
| 0.3189        | 4.0   | 59   | 0.3626          | 0.8875   |
| 0.2226        | 4.95  | 73   | 0.2638          | 0.9046   |
| 0.2394        | 5.97  | 88   | 0.3584          | 0.8802   |
| 0.2241        | 6.98  | 103  | 0.2821          | 0.9046   |
| 0.1815        | 8.0   | 118  | 0.2138          | 0.9218   |
| 0.1862        | 8.95  | 132  | 0.2738          | 0.9046   |
| 0.1942        | 9.49  | 140  | 0.2553          | 0.9120   |


### Framework versions

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