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# swin-tiny-patch4-window7-224-swinnn

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0883
- Accuracy: 0.8232

## 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: 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: 50

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 0.2802        | 0.9979  | 351   | 0.2783          | 0.3222   |
| 0.2702        | 1.9986  | 703   | 0.2652          | 0.376    |
| 0.2565        | 2.9993  | 1055  | 0.2474          | 0.431    |
| 0.2448        | 4.0     | 1407  | 0.2358          | 0.4558   |
| 0.2433        | 4.9979  | 1758  | 0.2223          | 0.4994   |
| 0.2095        | 5.9986  | 2110  | 0.2058          | 0.5434   |
| 0.2197        | 6.9993  | 2462  | 0.1963          | 0.568    |
| 0.2093        | 8.0     | 2814  | 0.1906          | 0.5764   |
| 0.2047        | 8.9979  | 3165  | 0.1888          | 0.5874   |
| 0.1952        | 9.9986  | 3517  | 0.1743          | 0.6192   |
| 0.1926        | 10.9993 | 3869  | 0.1740          | 0.6234   |
| 0.1838        | 12.0    | 4221  | 0.1667          | 0.6448   |
| 0.1822        | 12.9979 | 4572  | 0.1629          | 0.6468   |
| 0.1838        | 13.9986 | 4924  | 0.1587          | 0.6638   |
| 0.1689        | 14.9993 | 5276  | 0.1563          | 0.675    |
| 0.1697        | 16.0    | 5628  | 0.1472          | 0.6916   |
| 0.1643        | 16.9979 | 5979  | 0.1435          | 0.6912   |
| 0.1655        | 17.9986 | 6331  | 0.1395          | 0.706    |
| 0.1555        | 18.9993 | 6683  | 0.1371          | 0.714    |
| 0.1577        | 20.0    | 7035  | 0.1321          | 0.7258   |
| 0.1575        | 20.9979 | 7386  | 0.1318          | 0.7284   |
| 0.141         | 21.9986 | 7738  | 0.1228          | 0.7438   |
| 0.151         | 22.9993 | 8090  | 0.1260          | 0.7392   |
| 0.1403        | 24.0    | 8442  | 0.1178          | 0.7558   |
| 0.1434        | 24.9979 | 8793  | 0.1185          | 0.7534   |
| 0.1465        | 25.9986 | 9145  | 0.1162          | 0.759    |
| 0.1362        | 26.9993 | 9497  | 0.1121          | 0.769    |
| 0.138         | 28.0    | 9849  | 0.1099          | 0.769    |
| 0.1293        | 28.9979 | 10200 | 0.1094          | 0.7754   |
| 0.1273        | 29.9986 | 10552 | 0.1091          | 0.7768   |
| 0.1363        | 30.9993 | 10904 | 0.1078          | 0.7766   |
| 0.1293        | 32.0    | 11256 | 0.1091          | 0.7736   |
| 0.1275        | 32.9979 | 11607 | 0.1068          | 0.7806   |
| 0.1263        | 33.9986 | 11959 | 0.1040          | 0.7888   |
| 0.1243        | 34.9993 | 12311 | 0.1019          | 0.7954   |
| 0.1237        | 36.0    | 12663 | 0.1016          | 0.7958   |
| 0.1243        | 36.9979 | 13014 | 0.0993          | 0.7988   |
| 0.1194        | 37.9986 | 13366 | 0.1011          | 0.7986   |
| 0.1213        | 38.9993 | 13718 | 0.0959          | 0.8064   |
| 0.1155        | 40.0    | 14070 | 0.0942          | 0.8108   |
| 0.1179        | 40.9979 | 14421 | 0.0950          | 0.8072   |
| 0.1057        | 41.9986 | 14773 | 0.0924          | 0.8166   |
| 0.1042        | 42.9993 | 15125 | 0.0924          | 0.8152   |
| 0.1151        | 44.0    | 15477 | 0.0928          | 0.8132   |
| 0.1122        | 44.9979 | 15828 | 0.0920          | 0.8146   |
| 0.11          | 45.9986 | 16180 | 0.0906          | 0.8152   |
| 0.1096        | 46.9993 | 16532 | 0.0894          | 0.82     |
| 0.1082        | 48.0    | 16884 | 0.0885          | 0.821    |
| 0.108         | 48.9979 | 17235 | 0.0886          | 0.8204   |
| 0.112         | 49.8934 | 17550 | 0.0883          | 0.8232   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.1.0a0+32f93b1
- Datasets 3.1.0
- Tokenizers 0.20.3

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7 label_8 label_9