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# cards_bottom_right_swin-tiny-patch4-window7-224-finetuned-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: 0.9317
- Accuracy: 0.6079

## 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: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4965        | 1.0   | 1338  | 1.3516          | 0.4156   |
| 1.4486        | 2.0   | 2677  | 1.1784          | 0.4938   |
| 1.4384        | 3.0   | 4015  | 1.1050          | 0.5223   |
| 1.4538        | 4.0   | 5354  | 1.0751          | 0.5433   |
| 1.3928        | 5.0   | 6692  | 1.0604          | 0.5440   |
| 1.4148        | 6.0   | 8031  | 1.0459          | 0.5523   |
| 1.3921        | 7.0   | 9369  | 1.0464          | 0.5501   |
| 1.3812        | 8.0   | 10708 | 1.0461          | 0.5491   |
| 1.3494        | 9.0   | 12046 | 1.0445          | 0.5486   |
| 1.3555        | 10.0  | 13385 | 0.9973          | 0.5693   |
| 1.3303        | 11.0  | 14723 | 0.9952          | 0.5719   |
| 1.3575        | 12.0  | 16062 | 1.0317          | 0.5574   |
| 1.3129        | 13.0  | 17400 | 0.9851          | 0.5813   |
| 1.3439        | 14.0  | 18739 | 1.0510          | 0.5523   |
| 1.3371        | 15.0  | 20077 | 0.9820          | 0.5795   |
| 1.2835        | 16.0  | 21416 | 0.9886          | 0.5738   |
| 1.3002        | 17.0  | 22754 | 0.9685          | 0.5869   |
| 1.289         | 18.0  | 24093 | 0.9519          | 0.5941   |
| 1.3007        | 19.0  | 25431 | 0.9855          | 0.5800   |
| 1.2927        | 20.0  | 26770 | 0.9499          | 0.5925   |
| 1.2985        | 21.0  | 28108 | 0.9669          | 0.5854   |
| 1.2957        | 22.0  | 29447 | 0.9551          | 0.5903   |
| 1.2579        | 23.0  | 30785 | 0.9300          | 0.6053   |
| 1.2475        | 24.0  | 32124 | 0.9296          | 0.6049   |
| 1.2227        | 25.0  | 33462 | 0.9317          | 0.6079   |
| 1.2069        | 26.0  | 34801 | 0.9609          | 0.5887   |
| 1.2156        | 27.0  | 36139 | 0.9297          | 0.6052   |
| 1.25          | 28.0  | 37478 | 0.9300          | 0.6062   |
| 1.2394        | 29.0  | 38816 | 0.9238          | 0.6071   |
| 1.209         | 29.99 | 40140 | 0.9284          | 0.6064   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2

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