---
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-binary
  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: 0.9714285714285714
---

<!-- 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-binary

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: 0.1138
- Accuracy: 0.9714

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1286        | 0.96  | 12   | 0.1138          | 0.9714   |
| 0.1267        | 2.0   | 25   | 0.1283          | 0.9657   |
| 0.121         | 2.96  | 37   | 0.1124          | 0.9657   |
| 0.1142        | 4.0   | 50   | 0.1151          | 0.9657   |
| 0.1069        | 4.96  | 62   | 0.1063          | 0.96     |
| 0.1038        | 6.0   | 75   | 0.1210          | 0.96     |
| 0.0935        | 6.96  | 87   | 0.1150          | 0.96     |
| 0.1042        | 8.0   | 100  | 0.1038          | 0.9657   |
| 0.0945        | 8.96  | 112  | 0.1071          | 0.96     |
| 0.0891        | 9.6   | 120  | 0.1077          | 0.96     |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1