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# swin-base-patch4-window7-224_rice-leaf-disease-augmented-v4_v5_pft

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4024
- Accuracy: 0.8490

## 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: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 256
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0846        | 0.5   | 64   | 1.9602          | 0.2483   |
| 1.7504        | 1.0   | 128  | 1.5308          | 0.5034   |
| 1.3704        | 1.5   | 192  | 1.1825          | 0.6107   |
| 1.113         | 2.0   | 256  | 0.9313          | 0.7148   |
| 0.9305        | 2.5   | 320  | 0.8132          | 0.7617   |
| 0.8171        | 3.0   | 384  | 0.7214          | 0.7651   |
| 0.7497        | 3.5   | 448  | 0.6650          | 0.7785   |
| 0.7039        | 4.0   | 512  | 0.6244          | 0.8188   |
| 0.6696        | 4.5   | 576  | 0.6003          | 0.8188   |
| 0.649         | 5.0   | 640  | 0.5976          | 0.8121   |
| 0.6334        | 5.5   | 704  | 0.6032          | 0.8020   |
| 0.6256        | 6.0   | 768  | 0.5859          | 0.8188   |
| 0.6417        | 6.5   | 832  | 0.5851          | 0.8188   |
| 0.5991        | 7.0   | 896  | 0.5835          | 0.8154   |
| 0.6014        | 7.5   | 960  | 0.5394          | 0.8322   |
| 0.5614        | 8.0   | 1024 | 0.5211          | 0.8356   |
| 0.536         | 8.5   | 1088 | 0.5184          | 0.8121   |
| 0.5443        | 9.0   | 1152 | 0.5256          | 0.8154   |
| 0.5129        | 9.5   | 1216 | 0.5026          | 0.8221   |
| 0.5084        | 10.0  | 1280 | 0.5028          | 0.8188   |
| 0.5081        | 10.5  | 1344 | 0.4996          | 0.8188   |
| 0.4936        | 11.0  | 1408 | 0.5004          | 0.8188   |
| 0.5           | 11.5  | 1472 | 0.5091          | 0.8121   |
| 0.4934        | 12.0  | 1536 | 0.4892          | 0.8356   |
| 0.4831        | 12.5  | 1600 | 0.4736          | 0.8322   |
| 0.4638        | 13.0  | 1664 | 0.4727          | 0.8255   |
| 0.4549        | 13.5  | 1728 | 0.4552          | 0.8456   |
| 0.4454        | 14.0  | 1792 | 0.4646          | 0.8322   |
| 0.44          | 14.5  | 1856 | 0.4610          | 0.8322   |
| 0.4304        | 15.0  | 1920 | 0.4574          | 0.8356   |
| 0.4255        | 15.5  | 1984 | 0.4550          | 0.8356   |
| 0.4353        | 16.0  | 2048 | 0.4548          | 0.8356   |
| 0.4456        | 16.5  | 2112 | 0.4465          | 0.8322   |
| 0.4047        | 17.0  | 2176 | 0.4619          | 0.8255   |
| 0.4119        | 17.5  | 2240 | 0.4497          | 0.8389   |
| 0.4009        | 18.0  | 2304 | 0.4329          | 0.8423   |
| 0.3901        | 18.5  | 2368 | 0.4286          | 0.8456   |
| 0.3936        | 19.0  | 2432 | 0.4318          | 0.8456   |
| 0.3761        | 19.5  | 2496 | 0.4297          | 0.8456   |
| 0.3885        | 20.0  | 2560 | 0.4279          | 0.8456   |
| 0.3806        | 20.5  | 2624 | 0.4271          | 0.8456   |
| 0.3779        | 21.0  | 2688 | 0.4352          | 0.8523   |
| 0.3746        | 21.5  | 2752 | 0.4256          | 0.8490   |
| 0.3708        | 22.0  | 2816 | 0.4253          | 0.8557   |
| 0.362         | 22.5  | 2880 | 0.4205          | 0.8490   |
| 0.3558        | 23.0  | 2944 | 0.4122          | 0.8490   |
| 0.3507        | 23.5  | 3008 | 0.4147          | 0.8423   |
| 0.3481        | 24.0  | 3072 | 0.4134          | 0.8456   |
| 0.3452        | 24.5  | 3136 | 0.4120          | 0.8456   |
| 0.3437        | 25.0  | 3200 | 0.4117          | 0.8490   |
| 0.3499        | 25.5  | 3264 | 0.4164          | 0.8523   |
| 0.3373        | 26.0  | 3328 | 0.4109          | 0.8490   |
| 0.3468        | 26.5  | 3392 | 0.3999          | 0.8523   |
| 0.3297        | 27.0  | 3456 | 0.4079          | 0.8523   |
| 0.329         | 27.5  | 3520 | 0.3997          | 0.8423   |
| 0.3293        | 28.0  | 3584 | 0.4051          | 0.8423   |
| 0.3147        | 28.5  | 3648 | 0.3987          | 0.8523   |
| 0.3239        | 29.0  | 3712 | 0.4013          | 0.8523   |
| 0.3147        | 29.5  | 3776 | 0.4031          | 0.8490   |
| 0.3167        | 30.0  | 3840 | 0.4024          | 0.8490   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1

bacterial leaf blight brown spot healthy rice leaf leaf blast leaf scald narrow brown leaf spot rice hispa sheath blight