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# vit-base-patch16-224_rice-leaf-disease-augmented-v4_v5_pft

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4332
- Accuracy: 0.8456

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1701        | 0.5   | 64   | 1.9984          | 0.2349   |
| 1.878         | 1.0   | 128  | 1.6113          | 0.4698   |
| 1.4921        | 1.5   | 192  | 1.2635          | 0.6174   |
| 1.2126        | 2.0   | 256  | 1.0178          | 0.6812   |
| 0.9922        | 2.5   | 320  | 0.8928          | 0.7148   |
| 0.8858        | 3.0   | 384  | 0.7883          | 0.7483   |
| 0.7966        | 3.5   | 448  | 0.7408          | 0.7517   |
| 0.7427        | 4.0   | 512  | 0.6912          | 0.7651   |
| 0.7077        | 4.5   | 576  | 0.6795          | 0.7718   |
| 0.6796        | 5.0   | 640  | 0.6647          | 0.7785   |
| 0.6597        | 5.5   | 704  | 0.6684          | 0.7752   |
| 0.6652        | 6.0   | 768  | 0.6535          | 0.7752   |
| 0.6762        | 6.5   | 832  | 0.6533          | 0.7752   |
| 0.6277        | 7.0   | 896  | 0.6356          | 0.7886   |
| 0.6264        | 7.5   | 960  | 0.6008          | 0.7987   |
| 0.5906        | 8.0   | 1024 | 0.5791          | 0.8154   |
| 0.5596        | 8.5   | 1088 | 0.5789          | 0.8054   |
| 0.5619        | 9.0   | 1152 | 0.5785          | 0.7987   |
| 0.5381        | 9.5   | 1216 | 0.5532          | 0.8121   |
| 0.5275        | 10.0  | 1280 | 0.5591          | 0.8087   |
| 0.5183        | 10.5  | 1344 | 0.5555          | 0.8054   |
| 0.5236        | 11.0  | 1408 | 0.5551          | 0.8087   |
| 0.5198        | 11.5  | 1472 | 0.5649          | 0.8020   |
| 0.5128        | 12.0  | 1536 | 0.5312          | 0.8356   |
| 0.4932        | 12.5  | 1600 | 0.5238          | 0.8054   |
| 0.4854        | 13.0  | 1664 | 0.5234          | 0.8121   |
| 0.4674        | 13.5  | 1728 | 0.5142          | 0.8221   |
| 0.4614        | 14.0  | 1792 | 0.5109          | 0.8154   |
| 0.4558        | 14.5  | 1856 | 0.5095          | 0.8289   |
| 0.4419        | 15.0  | 1920 | 0.5043          | 0.8188   |
| 0.4362        | 15.5  | 1984 | 0.5034          | 0.8221   |
| 0.4496        | 16.0  | 2048 | 0.5032          | 0.8221   |
| 0.4484        | 16.5  | 2112 | 0.5017          | 0.8221   |
| 0.4325        | 17.0  | 2176 | 0.5015          | 0.8289   |
| 0.428         | 17.5  | 2240 | 0.4967          | 0.8221   |
| 0.4091        | 18.0  | 2304 | 0.4704          | 0.8356   |
| 0.405         | 18.5  | 2368 | 0.4792          | 0.8289   |
| 0.4012        | 19.0  | 2432 | 0.4750          | 0.8322   |
| 0.3887        | 19.5  | 2496 | 0.4750          | 0.8289   |
| 0.3986        | 20.0  | 2560 | 0.4711          | 0.8255   |
| 0.3983        | 20.5  | 2624 | 0.4713          | 0.8255   |
| 0.3857        | 21.0  | 2688 | 0.4750          | 0.8289   |
| 0.3925        | 21.5  | 2752 | 0.4506          | 0.8456   |
| 0.3787        | 22.0  | 2816 | 0.4622          | 0.8255   |
| 0.368         | 22.5  | 2880 | 0.4583          | 0.8389   |
| 0.3702        | 23.0  | 2944 | 0.4479          | 0.8423   |
| 0.3591        | 23.5  | 3008 | 0.4485          | 0.8389   |
| 0.3588        | 24.0  | 3072 | 0.4534          | 0.8356   |
| 0.3517        | 24.5  | 3136 | 0.4496          | 0.8356   |
| 0.3546        | 25.0  | 3200 | 0.4482          | 0.8389   |
| 0.3636        | 25.5  | 3264 | 0.4518          | 0.8356   |
| 0.3435        | 26.0  | 3328 | 0.4495          | 0.8322   |
| 0.3423        | 26.5  | 3392 | 0.4427          | 0.8322   |
| 0.3477        | 27.0  | 3456 | 0.4365          | 0.8423   |
| 0.3405        | 27.5  | 3520 | 0.4380          | 0.8389   |
| 0.3254        | 28.0  | 3584 | 0.4366          | 0.8389   |
| 0.3245        | 28.5  | 3648 | 0.4316          | 0.8423   |
| 0.3265        | 29.0  | 3712 | 0.4305          | 0.8423   |
| 0.3193        | 29.5  | 3776 | 0.4339          | 0.8456   |
| 0.3244        | 30.0  | 3840 | 0.4332          | 0.8456   |


### 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