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# 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: 0.2851
- Accuracy: 0.9094

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.0421        | 0.9941  | 127  | 1.9090          | 0.3566   |
| 1.2943        | 1.9922  | 254  | 1.2209          | 0.5679   |
| 0.8757        | 2.9902  | 381  | 0.8373          | 0.7108   |
| 0.7362        | 3.9961  | 509  | 0.6260          | 0.7967   |
| 0.6011        | 4.9941  | 636  | 0.5550          | 0.8049   |
| 0.5267        | 5.9922  | 763  | 0.4797          | 0.8339   |
| 0.4969        | 6.9902  | 890  | 0.4508          | 0.8583   |
| 0.4418        | 7.9961  | 1018 | 0.4243          | 0.8571   |
| 0.4564        | 8.9941  | 1145 | 0.4035          | 0.8618   |
| 0.4199        | 9.9922  | 1272 | 0.3678          | 0.8804   |
| 0.3929        | 10.9902 | 1399 | 0.3479          | 0.8897   |
| 0.3578        | 11.9961 | 1527 | 0.3355          | 0.8931   |
| 0.3405        | 12.9941 | 1654 | 0.3173          | 0.8955   |
| 0.3399        | 13.9922 | 1781 | 0.3177          | 0.9048   |
| 0.3219        | 14.9902 | 1908 | 0.3354          | 0.8943   |
| 0.3296        | 15.9961 | 2036 | 0.3175          | 0.8978   |
| 0.3259        | 16.9941 | 2163 | 0.2908          | 0.9048   |
| 0.3201        | 17.9922 | 2290 | 0.2883          | 0.9082   |
| 0.2922        | 18.9902 | 2417 | 0.2945          | 0.9013   |
| 0.3204        | 19.9961 | 2545 | 0.2961          | 0.9013   |
| 0.2926        | 20.9941 | 2672 | 0.2934          | 0.9048   |
| 0.3083        | 21.9922 | 2799 | 0.2960          | 0.9024   |
| 0.3174        | 22.9902 | 2926 | 0.2876          | 0.9059   |
| 0.2693        | 23.9961 | 3054 | 0.2896          | 0.9036   |
| 0.2807        | 24.9941 | 3181 | 0.2852          | 0.8990   |
| 0.289         | 25.9922 | 3308 | 0.2847          | 0.9048   |
| 0.2829        | 26.9902 | 3435 | 0.2888          | 0.9048   |
| 0.2749        | 27.9961 | 3563 | 0.2898          | 0.9059   |
| 0.2726        | 28.9941 | 3690 | 0.2780          | 0.9094   |
| 0.2744        | 29.9374 | 3810 | 0.2851          | 0.9094   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3

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