---
library_name: transformers
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: 0.8709677419354839
---

<!-- 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: 0.3968
- Accuracy: 0.8710

## 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: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8889  | 2    | 1.7756          | 0.2258   |
| No log        | 1.7778  | 4    | 1.6784          | 0.2581   |
| No log        | 2.6667  | 6    | 1.5861          | 0.3226   |
| No log        | 4.0     | 9    | 1.3571          | 0.4194   |
| No log        | 4.8889  | 11   | 1.0993          | 0.5484   |
| No log        | 5.7778  | 13   | 0.9242          | 0.6452   |
| 1.4667        | 6.6667  | 15   | 0.7538          | 0.7097   |
| 1.4667        | 8.0     | 18   | 0.6294          | 0.7742   |
| 1.4667        | 8.8889  | 20   | 0.5326          | 0.7097   |
| 1.4667        | 9.7778  | 22   | 0.4848          | 0.7419   |
| 1.4667        | 10.6667 | 24   | 0.4832          | 0.7742   |
| 1.4667        | 12.0    | 27   | 0.4483          | 0.7742   |
| 1.4667        | 12.8889 | 29   | 0.4296          | 0.7742   |
| 0.5925        | 13.7778 | 31   | 0.4023          | 0.7742   |
| 0.5925        | 14.6667 | 33   | 0.4111          | 0.8387   |
| 0.5925        | 16.0    | 36   | 0.3873          | 0.8065   |
| 0.5925        | 16.8889 | 38   | 0.4029          | 0.8065   |
| 0.5925        | 17.7778 | 40   | 0.4065          | 0.8065   |
| 0.5925        | 18.6667 | 42   | 0.3864          | 0.8065   |
| 0.3285        | 20.0    | 45   | 0.3968          | 0.8710   |
| 0.3285        | 20.8889 | 47   | 0.3930          | 0.8710   |
| 0.3285        | 21.7778 | 49   | 0.3871          | 0.8710   |
| 0.3285        | 22.6667 | 51   | 0.3779          | 0.8065   |
| 0.3285        | 24.0    | 54   | 0.3698          | 0.8065   |
| 0.3285        | 24.8889 | 56   | 0.3726          | 0.8387   |
| 0.3285        | 25.7778 | 58   | 0.3732          | 0.8387   |
| 0.2621        | 26.6667 | 60   | 0.3732          | 0.8387   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0