---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-mobile-eye-tracking-dataset-v2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.598512173128945
---

<!-- 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-mobile-eye-tracking-dataset-v2

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 image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6732
- Accuracy: 0.5985

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6726        | 1.0   | 329  | 0.6758          | 0.5985   |
| 0.6773        | 2.0   | 658  | 0.6738          | 0.5985   |
| 0.6701        | 3.0   | 987  | 0.6736          | 0.5985   |
| 0.6734        | 4.0   | 1317 | 0.6735          | 0.5985   |
| 0.671         | 5.0   | 1646 | 0.6738          | 0.5985   |
| 0.6725        | 6.0   | 1975 | 0.6740          | 0.5985   |
| 0.6702        | 7.0   | 2304 | 0.6737          | 0.5985   |
| 0.6708        | 8.0   | 2634 | 0.6733          | 0.5983   |
| 0.6732        | 9.0   | 2963 | 0.6735          | 0.5985   |
| 0.671         | 9.99  | 3290 | 0.6732          | 0.5985   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1