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# mobilevit-small_rice-leaf-disease-augmented-v4_fft

This model is a fine-tuned version of [apple/mobilevit-small](https://huggingface.co/apple/mobilevit-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4089
- Accuracy: 0.9295

## 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: 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 | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.0561        | 0.5   | 64   | 0.2886   | 2.0213          |
| 1.9819        | 1.0   | 128  | 0.5503   | 1.8788          |
| 1.771         | 1.5   | 192  | 0.6107   | 1.5291          |
| 1.3911        | 2.0   | 256  | 0.7349   | 1.0706          |
| 1.0026        | 2.5   | 320  | 0.8054   | 0.7560          |
| 0.7657        | 3.0   | 384  | 0.8356   | 0.6180          |
| 0.6082        | 3.5   | 448  | 0.8389   | 0.5422          |
| 0.5313        | 4.0   | 512  | 0.8523   | 0.4946          |
| 0.4623        | 4.5   | 576  | 0.8758   | 0.4512          |
| 0.4212        | 5.0   | 640  | 0.8792   | 0.4322          |
| 0.4025        | 5.5   | 704  | 0.8893   | 0.4259          |
| 0.3892        | 6.0   | 768  | 0.8859   | 0.4238          |
| 0.3959        | 6.5   | 832  | 0.8859   | 0.4083          |
| 0.3279        | 7.0   | 896  | 0.8826   | 0.3750          |
| 0.2793        | 7.5   | 960  | 0.8993   | 0.3350          |
| 0.222         | 8.0   | 1024 | 0.8960   | 0.3208          |
| 0.1862        | 8.5   | 1088 | 0.8993   | 0.3128          |
| 0.1717        | 9.0   | 1152 | 0.9027   | 0.3049          |
| 0.1408        | 9.5   | 1216 | 0.9027   | 0.3010          |
| 0.1507        | 10.0  | 1280 | 0.9161   | 0.3240          |
| 0.1369        | 10.5  | 1344 | 0.9060   | 0.3063          |
| 0.1389        | 11.0  | 1408 | 0.9060   | 0.3045          |
| 0.1199        | 11.5  | 1472 | 0.9094   | 0.3062          |
| 0.1003        | 12.0  | 1536 | 0.9128   | 0.3131          |
| 0.0756        | 12.5  | 1600 | 0.9228   | 0.3002          |
| 0.0636        | 13.0  | 1664 | 0.9128   | 0.3177          |
| 0.058         | 13.5  | 1728 | 0.9228   | 0.3143          |
| 0.0566        | 14.0  | 1792 | 0.9195   | 0.3136          |
| 0.0516        | 14.5  | 1856 | 0.9161   | 0.3447          |
| 0.0426        | 15.0  | 1920 | 0.9228   | 0.2911          |
| 0.0513        | 15.5  | 1984 | 0.3028   | 0.9228          |
| 0.0447        | 16.0  | 2048 | 0.3328   | 0.9195          |
| 0.0332        | 16.5  | 2112 | 0.3193   | 0.9262          |
| 0.0358        | 17.0  | 2176 | 0.3385   | 0.9161          |
| 0.0343        | 17.5  | 2240 | 0.3297   | 0.9295          |
| 0.0291        | 18.0  | 2304 | 0.3518   | 0.9161          |
| 0.0287        | 18.5  | 2368 | 0.3224   | 0.9195          |
| 0.0197        | 19.0  | 2432 | 0.3099   | 0.9228          |
| 0.0223        | 19.5  | 2496 | 0.3305   | 0.9295          |
| 0.0282        | 20.0  | 2560 | 0.3378   | 0.9161          |
| 0.0231        | 20.5  | 2624 | 0.3077   | 0.9228          |
| 0.0251        | 21.0  | 2688 | 0.3520   | 0.9161          |
| 0.021         | 21.5  | 2752 | 0.3506   | 0.9228          |
| 0.0222        | 22.0  | 2816 | 0.3561   | 0.9128          |
| 0.016         | 22.5  | 2880 | 0.3482   | 0.9195          |
| 0.0163        | 23.0  | 2944 | 0.3429   | 0.9228          |
| 0.0114        | 23.5  | 3008 | 0.3839   | 0.9329          |
| 0.0106        | 24.0  | 3072 | 0.4066   | 0.9262          |
| 0.0111        | 24.5  | 3136 | 0.4003   | 0.9329          |
| 0.009         | 25.0  | 3200 | 0.4000   | 0.9262          |
| 0.0088        | 25.5  | 3264 | 0.3667   | 0.9228          |
| 0.0057        | 26.0  | 3328 | 0.3587   | 0.9195          |
| 0.0073        | 26.5  | 3392 | 0.3686   | 0.9329          |
| 0.0085        | 27.0  | 3456 | 0.3676   | 0.9195          |
| 0.0087        | 27.5  | 3520 | 0.4251   | 0.9262          |
| 0.0061        | 28.0  | 3584 | 0.3879   | 0.9195          |
| 0.0062        | 28.5  | 3648 | 0.3865   | 0.9195          |
| 0.0068        | 29.0  | 3712 | 0.3943   | 0.9262          |
| 0.0092        | 29.5  | 3776 | 0.4064   | 0.9228          |
| 0.0078        | 30.0  | 3840 | 0.4089   | 0.9295          |


### 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