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

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: 0.8963
- Accuracy: 0.7324

## 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: 100

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8889  | 6    | 4.2849          | 0.0047   |
| 4.3139        | 1.9259  | 13   | 4.1846          | 0.0329   |
| 4.1651        | 2.9630  | 20   | 4.0585          | 0.0563   |
| 4.1651        | 4.0     | 27   | 3.9527          | 0.0610   |
| 3.9272        | 4.8889  | 33   | 3.8813          | 0.0610   |
| 3.7461        | 5.9259  | 40   | 3.7536          | 0.0845   |
| 3.7461        | 6.9630  | 47   | 3.6486          | 0.1080   |
| 3.5254        | 8.0     | 54   | 3.5603          | 0.1362   |
| 3.3478        | 8.8889  | 60   | 3.4566          | 0.1362   |
| 3.3478        | 9.9259  | 67   | 3.2986          | 0.1502   |
| 3.0423        | 10.9630 | 74   | 3.2166          | 0.1549   |
| 2.7931        | 12.0    | 81   | 3.0203          | 0.2160   |
| 2.7931        | 12.8889 | 87   | 2.8991          | 0.2911   |
| 2.541         | 13.9259 | 94   | 2.7941          | 0.2911   |
| 2.3487        | 14.9630 | 101  | 2.7337          | 0.2911   |
| 2.3487        | 16.0    | 108  | 2.5401          | 0.3662   |
| 2.1043        | 16.8889 | 114  | 2.5088          | 0.3803   |
| 1.8892        | 17.9259 | 121  | 2.3596          | 0.4131   |
| 1.8892        | 18.9630 | 128  | 2.3180          | 0.4178   |
| 1.7167        | 20.0    | 135  | 2.1820          | 0.4272   |
| 1.5748        | 20.8889 | 141  | 2.0547          | 0.4413   |
| 1.5748        | 21.9259 | 148  | 1.9472          | 0.4930   |
| 1.4052        | 22.9630 | 155  | 1.9053          | 0.4883   |
| 1.2535        | 24.0    | 162  | 1.8179          | 0.5117   |
| 1.2535        | 24.8889 | 168  | 1.7600          | 0.5305   |
| 1.1687        | 25.9259 | 175  | 1.6922          | 0.5493   |
| 1.0719        | 26.9630 | 182  | 1.6076          | 0.5587   |
| 1.0719        | 28.0    | 189  | 1.5316          | 0.5587   |
| 1.0577        | 28.8889 | 195  | 1.5365          | 0.5775   |
| 0.9558        | 29.9259 | 202  | 1.4488          | 0.6291   |
| 0.9558        | 30.9630 | 209  | 1.4185          | 0.6150   |
| 0.8771        | 32.0    | 216  | 1.3906          | 0.6056   |
| 0.8146        | 32.8889 | 222  | 1.3828          | 0.6150   |
| 0.8146        | 33.9259 | 229  | 1.3927          | 0.5822   |
| 0.8228        | 34.9630 | 236  | 1.3036          | 0.6385   |
| 0.6878        | 36.0    | 243  | 1.2240          | 0.6808   |
| 0.6878        | 36.8889 | 249  | 1.2388          | 0.6714   |
| 0.6471        | 37.9259 | 256  | 1.1345          | 0.6808   |
| 0.6102        | 38.9630 | 263  | 1.1815          | 0.6573   |
| 0.6599        | 40.0    | 270  | 1.1720          | 0.6526   |
| 0.6599        | 40.8889 | 276  | 1.1336          | 0.6526   |
| 0.5742        | 41.9259 | 283  | 1.0863          | 0.6714   |
| 0.5478        | 42.9630 | 290  | 1.0910          | 0.6714   |
| 0.5478        | 44.0    | 297  | 1.0746          | 0.6620   |
| 0.557         | 44.8889 | 303  | 1.0724          | 0.6808   |
| 0.5753        | 45.9259 | 310  | 1.0108          | 0.7136   |
| 0.5753        | 46.9630 | 317  | 1.1296          | 0.6432   |
| 0.5325        | 48.0    | 324  | 1.0361          | 0.6901   |
| 0.4349        | 48.8889 | 330  | 1.0237          | 0.6995   |
| 0.4349        | 49.9259 | 337  | 0.9790          | 0.7183   |
| 0.447         | 50.9630 | 344  | 1.0409          | 0.6808   |
| 0.4502        | 52.0    | 351  | 1.0467          | 0.6714   |
| 0.4502        | 52.8889 | 357  | 0.9773          | 0.7183   |
| 0.4345        | 53.9259 | 364  | 0.9931          | 0.6808   |
| 0.4557        | 54.9630 | 371  | 0.9685          | 0.7136   |
| 0.4557        | 56.0    | 378  | 0.9547          | 0.7371   |
| 0.4109        | 56.8889 | 384  | 1.0015          | 0.6948   |
| 0.4406        | 57.9259 | 391  | 0.9410          | 0.7230   |
| 0.4406        | 58.9630 | 398  | 0.9765          | 0.6808   |
| 0.4039        | 60.0    | 405  | 0.9505          | 0.7089   |
| 0.396         | 60.8889 | 411  | 0.9539          | 0.7183   |
| 0.396         | 61.9259 | 418  | 1.0391          | 0.6761   |
| 0.3958        | 62.9630 | 425  | 0.9576          | 0.7136   |
| 0.3763        | 64.0    | 432  | 0.9380          | 0.7230   |
| 0.3763        | 64.8889 | 438  | 0.9363          | 0.7277   |
| 0.3985        | 65.9259 | 445  | 0.9400          | 0.7089   |
| 0.3701        | 66.9630 | 452  | 0.9769          | 0.7183   |
| 0.3701        | 68.0    | 459  | 0.9604          | 0.7277   |
| 0.3729        | 68.8889 | 465  | 0.9883          | 0.7089   |
| 0.3958        | 69.9259 | 472  | 0.9516          | 0.7277   |
| 0.3958        | 70.9630 | 479  | 0.9252          | 0.7183   |
| 0.359         | 72.0    | 486  | 0.9196          | 0.7136   |
| 0.362         | 72.8889 | 492  | 0.9104          | 0.7230   |
| 0.362         | 73.9259 | 499  | 0.9255          | 0.7136   |
| 0.353         | 74.9630 | 506  | 0.9359          | 0.7089   |
| 0.345         | 76.0    | 513  | 0.9274          | 0.7230   |
| 0.345         | 76.8889 | 519  | 0.9206          | 0.7371   |
| 0.3414        | 77.9259 | 526  | 0.9229          | 0.7277   |
| 0.3298        | 78.9630 | 533  | 0.9102          | 0.7418   |
| 0.3394        | 80.0    | 540  | 0.8955          | 0.7512   |
| 0.3394        | 80.8889 | 546  | 0.8956          | 0.7371   |
| 0.3384        | 81.9259 | 553  | 0.8927          | 0.7277   |
| 0.3164        | 82.9630 | 560  | 0.8885          | 0.7418   |
| 0.3164        | 84.0    | 567  | 0.8941          | 0.7371   |
| 0.3055        | 84.8889 | 573  | 0.8963          | 0.7418   |
| 0.3355        | 85.9259 | 580  | 0.8992          | 0.7324   |
| 0.3355        | 86.9630 | 587  | 0.8988          | 0.7324   |
| 0.3101        | 88.0    | 594  | 0.8969          | 0.7324   |
| 0.3218        | 88.8889 | 600  | 0.8963          | 0.7324   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1

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