---
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-soccer-binary2
  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: 0.9719298245614035
---

<!-- 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-soccer-binary2

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: 0.1078
- Accuracy: 0.9719

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4085        | 0.99  | 20   | 0.1740          | 0.9544   |
| 0.1281        | 1.98  | 40   | 0.1078          | 0.9719   |
| 0.108         | 2.96  | 60   | 0.0978          | 0.9684   |
| 0.1077        | 4.0   | 81   | 0.1006          | 0.9684   |
| 0.0916        | 4.99  | 101  | 0.0954          | 0.9649   |
| 0.0824        | 5.98  | 121  | 0.0935          | 0.9684   |
| 0.0859        | 6.96  | 141  | 0.0975          | 0.9684   |
| 0.0927        | 8.0   | 162  | 0.0949          | 0.9684   |
| 0.0836        | 8.99  | 182  | 0.0928          | 0.9684   |
| 0.0958        | 9.88  | 200  | 0.0940          | 0.9684   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0