---
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-mobile-eye-tracking-dataset-v2
  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: 0.8653366583541147
---

<!-- 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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3944
- Accuracy: 0.8653

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3648        | 0.99  | 59   | 0.3998          | 0.8653   |
| 0.3789        | 2.0   | 119  | 0.4005          | 0.8653   |
| 0.3572        | 2.99  | 178  | 0.4006          | 0.8653   |
| 0.3842        | 4.0   | 238  | 0.3905          | 0.8653   |
| 0.356         | 4.99  | 297  | 0.3894          | 0.8653   |
| 0.3564        | 6.0   | 357  | 0.3936          | 0.8653   |
| 0.3668        | 6.99  | 416  | 0.3934          | 0.8653   |
| 0.3538        | 8.0   | 476  | 0.3882          | 0.8653   |
| 0.353         | 8.99  | 535  | 0.3870          | 0.8653   |
| 0.3481        | 10.0  | 595  | 0.3867          | 0.8653   |
| 0.3315        | 10.99 | 654  | 0.3949          | 0.8653   |
| 0.3456        | 12.0  | 714  | 0.3919          | 0.8678   |
| 0.3329        | 12.99 | 773  | 0.3905          | 0.8653   |
| 0.3409        | 14.0  | 833  | 0.3930          | 0.8653   |
| 0.313         | 14.87 | 885  | 0.3944          | 0.8653   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0