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

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0479
- Accuracy: 0.9895

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1149        | 0.99  | 65   | 0.9590          | 0.7629   |
| 0.2653        | 2.0   | 131  | 0.1648          | 0.9532   |
| 0.1984        | 2.99  | 196  | 0.0894          | 0.9713   |
| 0.1719        | 4.0   | 262  | 0.0863          | 0.9685   |
| 0.1537        | 4.99  | 327  | 0.0810          | 0.9761   |
| 0.1162        | 6.0   | 393  | 0.0785          | 0.9771   |
| 0.1063        | 6.99  | 458  | 0.0835          | 0.9723   |
| 0.1392        | 8.0   | 524  | 0.0674          | 0.9761   |
| 0.1286        | 8.99  | 589  | 0.0788          | 0.9761   |
| 0.1294        | 10.0  | 655  | 0.0658          | 0.9790   |
| 0.0843        | 10.99 | 720  | 0.0735          | 0.9732   |
| 0.074         | 12.0  | 786  | 0.0636          | 0.9761   |
| 0.0734        | 12.99 | 851  | 0.1043          | 0.9751   |
| 0.0774        | 14.0  | 917  | 0.0898          | 0.9723   |
| 0.068         | 14.99 | 982  | 0.0719          | 0.9809   |
| 0.0821        | 16.0  | 1048 | 0.0956          | 0.9742   |
| 0.0576        | 16.99 | 1113 | 0.0725          | 0.9713   |
| 0.0652        | 18.0  | 1179 | 0.0957          | 0.9751   |
| 0.0712        | 18.99 | 1244 | 0.0809          | 0.9790   |
| 0.075         | 20.0  | 1310 | 0.1283          | 0.9675   |
| 0.0988        | 20.99 | 1375 | 0.0966          | 0.9742   |
| 0.0538        | 22.0  | 1441 | 0.1125          | 0.9761   |
| 0.0578        | 22.99 | 1506 | 0.0648          | 0.9828   |
| 0.0675        | 24.0  | 1572 | 0.0992          | 0.9799   |
| 0.0611        | 24.99 | 1637 | 0.0682          | 0.9818   |
| 0.0434        | 26.0  | 1703 | 0.0719          | 0.9809   |
| 0.0339        | 26.99 | 1768 | 0.0930          | 0.9780   |
| 0.0346        | 28.0  | 1834 | 0.0903          | 0.9799   |
| 0.0806        | 28.99 | 1899 | 0.0903          | 0.9799   |
| 0.0518        | 30.0  | 1965 | 0.0982          | 0.9790   |
| 0.0407        | 30.99 | 2030 | 0.0702          | 0.9828   |
| 0.0528        | 32.0  | 2096 | 0.0897          | 0.9761   |
| 0.0774        | 32.99 | 2161 | 0.0626          | 0.9818   |
| 0.053         | 34.0  | 2227 | 0.0576          | 0.9837   |
| 0.0512        | 34.99 | 2292 | 0.0707          | 0.9847   |
| 0.0388        | 36.0  | 2358 | 0.1040          | 0.9790   |
| 0.06          | 36.99 | 2423 | 0.0840          | 0.9799   |
| 0.0477        | 38.0  | 2489 | 0.0659          | 0.9857   |
| 0.0482        | 38.99 | 2554 | 0.0479          | 0.9895   |
| 0.0292        | 40.0  | 2620 | 0.0699          | 0.9818   |
| 0.0386        | 40.99 | 2685 | 0.1030          | 0.9837   |
| 0.0441        | 42.0  | 2751 | 0.0801          | 0.9818   |
| 0.0269        | 42.99 | 2816 | 0.1037          | 0.9809   |
| 0.0385        | 44.0  | 2882 | 0.0870          | 0.9799   |
| 0.0502        | 44.99 | 2947 | 0.1367          | 0.9771   |
| 0.0389        | 46.0  | 3013 | 0.1093          | 0.9771   |
| 0.0209        | 46.99 | 3078 | 0.0954          | 0.9837   |
| 0.0327        | 48.0  | 3144 | 0.0886          | 0.9857   |
| 0.0269        | 48.99 | 3209 | 0.0767          | 0.9828   |
| 0.0461        | 50.0  | 3275 | 0.0661          | 0.9857   |
| 0.0226        | 50.99 | 3340 | 0.0769          | 0.9818   |
| 0.0304        | 52.0  | 3406 | 0.0841          | 0.9828   |
| 0.0326        | 52.99 | 3471 | 0.1002          | 0.9828   |
| 0.0593        | 54.0  | 3537 | 0.0634          | 0.9847   |
| 0.0489        | 54.99 | 3602 | 0.0702          | 0.9837   |
| 0.0495        | 56.0  | 3668 | 0.1060          | 0.9809   |
| 0.0457        | 56.99 | 3733 | 0.0715          | 0.9866   |
| 0.0487        | 58.0  | 3799 | 0.0906          | 0.9818   |
| 0.0416        | 58.99 | 3864 | 0.0973          | 0.9790   |
| 0.0358        | 60.0  | 3930 | 0.0887          | 0.9857   |
| 0.0503        | 60.99 | 3995 | 0.0959          | 0.9809   |
| 0.0555        | 62.0  | 4061 | 0.1057          | 0.9780   |
| 0.0288        | 62.99 | 4126 | 0.0971          | 0.9799   |
| 0.0514        | 64.0  | 4192 | 0.0754          | 0.9847   |
| 0.0602        | 64.99 | 4257 | 0.0789          | 0.9837   |
| 0.0209        | 66.0  | 4323 | 0.1005          | 0.9837   |
| 0.0366        | 66.99 | 4388 | 0.1070          | 0.9818   |
| 0.031         | 68.0  | 4454 | 0.1018          | 0.9818   |
| 0.043         | 68.99 | 4519 | 0.1020          | 0.9828   |
| 0.0262        | 70.0  | 4585 | 0.0896          | 0.9837   |
| 0.0299        | 70.99 | 4650 | 0.0913          | 0.9837   |
| 0.0211        | 72.0  | 4716 | 0.0957          | 0.9857   |
| 0.0351        | 72.99 | 4781 | 0.1180          | 0.9818   |
| 0.0498        | 74.0  | 4847 | 0.1056          | 0.9828   |
| 0.0174        | 74.99 | 4912 | 0.1032          | 0.9809   |
| 0.0368        | 76.0  | 4978 | 0.1071          | 0.9790   |
| 0.0367        | 76.99 | 5043 | 0.0987          | 0.9828   |
| 0.027         | 78.0  | 5109 | 0.1037          | 0.9818   |
| 0.0225        | 78.99 | 5174 | 0.1129          | 0.9809   |
| 0.0241        | 80.0  | 5240 | 0.1202          | 0.9828   |
| 0.026         | 80.99 | 5305 | 0.1219          | 0.9790   |
| 0.0223        | 82.0  | 5371 | 0.1194          | 0.9799   |
| 0.0454        | 82.99 | 5436 | 0.1148          | 0.9790   |
| 0.019         | 84.0  | 5502 | 0.1168          | 0.9818   |
| 0.0269        | 84.99 | 5567 | 0.1246          | 0.9799   |
| 0.0403        | 86.0  | 5633 | 0.1301          | 0.9790   |
| 0.0294        | 86.99 | 5698 | 0.1204          | 0.9799   |
| 0.0501        | 88.0  | 5764 | 0.1168          | 0.9790   |
| 0.0361        | 88.99 | 5829 | 0.1143          | 0.9818   |
| 0.0278        | 90.0  | 5895 | 0.1029          | 0.9799   |
| 0.0267        | 90.99 | 5960 | 0.0991          | 0.9818   |
| 0.0308        | 92.0  | 6026 | 0.1028          | 0.9828   |
| 0.0246        | 92.99 | 6091 | 0.1031          | 0.9809   |
| 0.0283        | 94.0  | 6157 | 0.1035          | 0.9818   |
| 0.0278        | 94.99 | 6222 | 0.0999          | 0.9818   |
| 0.0221        | 96.0  | 6288 | 0.1007          | 0.9809   |
| 0.0197        | 96.99 | 6353 | 0.0989          | 0.9818   |
| 0.0435        | 98.0  | 6419 | 0.0986          | 0.9818   |
| 0.0266        | 98.99 | 6484 | 0.0987          | 0.9818   |
| 0.0334        | 99.24 | 6500 | 0.0987          | 0.9818   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0

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