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# swin-tiny-patch4-window7-224-finetuned-cp1

This model is a fine-tuned version of [Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1](https://huggingface.co/Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3628
- Accuracy: 0.8667

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 3    | 0.4305          | 0.8222   |
| No log        | 1.85  | 6    | 0.4510          | 0.8      |
| No log        | 2.77  | 9    | 0.4329          | 0.7778   |
| 0.3489        | 4.0   | 13   | 0.4965          | 0.7778   |
| 0.3489        | 4.92  | 16   | 0.4247          | 0.8      |
| 0.3489        | 5.85  | 19   | 0.3559          | 0.8444   |
| 0.2872        | 6.77  | 22   | 0.3628          | 0.8667   |
| 0.2872        | 8.0   | 26   | 0.3511          | 0.8667   |
| 0.2872        | 8.92  | 29   | 0.3538          | 0.8667   |
| 0.3071        | 9.85  | 32   | 0.3644          | 0.8222   |
| 0.3071        | 10.77 | 35   | 0.3860          | 0.8222   |
| 0.3071        | 12.0  | 39   | 0.5917          | 0.8      |
| 0.2765        | 12.92 | 42   | 0.5149          | 0.7778   |
| 0.2765        | 13.85 | 45   | 0.5605          | 0.7556   |
| 0.2765        | 14.77 | 48   | 0.4737          | 0.8      |
| 0.2637        | 16.0  | 52   | 0.4109          | 0.8444   |
| 0.2637        | 16.92 | 55   | 0.3584          | 0.8222   |
| 0.2637        | 17.85 | 58   | 0.3771          | 0.8222   |
| 0.2082        | 18.77 | 61   | 0.4406          | 0.8222   |
| 0.2082        | 20.0  | 65   | 0.3592          | 0.8222   |
| 0.2082        | 20.92 | 68   | 0.3302          | 0.8667   |
| 0.1944        | 21.85 | 71   | 0.3206          | 0.8444   |
| 0.1944        | 22.77 | 74   | 0.3215          | 0.8667   |
| 0.1944        | 24.0  | 78   | 0.3209          | 0.8667   |
| 0.2144        | 24.92 | 81   | 0.3327          | 0.8444   |
| 0.2144        | 25.85 | 84   | 0.3506          | 0.8444   |
| 0.2144        | 26.77 | 87   | 0.3545          | 0.8444   |
| 0.1754        | 27.69 | 90   | 0.3494          | 0.8444   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

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