---
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-wsdmhar
  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: 0.9297520661157025
---

<!-- 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-wsdmhar

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: 0.1990
- Accuracy: 0.9298

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7388        | 1.0   | 53   | 0.6308          | 0.7118   |
| 0.5099        | 2.0   | 106  | 0.3669          | 0.8485   |
| 0.4319        | 3.0   | 159  | 0.3324          | 0.8685   |
| 0.4002        | 4.0   | 212  | 0.2758          | 0.9029   |
| 0.3589        | 5.0   | 265  | 0.2503          | 0.9132   |
| 0.3096        | 6.0   | 318  | 0.2419          | 0.9136   |
| 0.2708        | 7.0   | 371  | 0.2277          | 0.9232   |
| 0.261         | 8.0   | 424  | 0.2168          | 0.9253   |
| 0.2526        | 9.0   | 477  | 0.2099          | 0.9246   |
| 0.2767        | 10.0  | 530  | 0.1990          | 0.9298   |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1