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# convnextv2-tiny-1k-224_rice-leaf-disease-augmented-v4_v5_fft

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2563
- Accuracy: 0.9530

## 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 | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9901        | 0.5   | 64   | 1.7784          | 0.4664   |
| 1.4592        | 1.0   | 128  | 1.0787          | 0.7248   |
| 0.7698        | 1.5   | 192  | 0.5368          | 0.8389   |
| 0.3994        | 2.0   | 256  | 0.3007          | 0.9094   |
| 0.1834        | 2.5   | 320  | 0.2267          | 0.9262   |
| 0.1011        | 3.0   | 384  | 0.2156          | 0.9195   |
| 0.0291        | 3.5   | 448  | 0.1964          | 0.9396   |
| 0.017         | 4.0   | 512  | 0.2273          | 0.9396   |
| 0.0036        | 4.5   | 576  | 0.2356          | 0.9329   |
| 0.0029        | 5.0   | 640  | 0.1751          | 0.9530   |
| 0.0013        | 5.5   | 704  | 0.1765          | 0.9530   |
| 0.0011        | 6.0   | 768  | 0.1850          | 0.9530   |
| 0.001         | 6.5   | 832  | 0.1829          | 0.9530   |
| 0.0009        | 7.0   | 896  | 0.1773          | 0.9564   |
| 0.0006        | 7.5   | 960  | 0.1920          | 0.9564   |
| 0.0004        | 8.0   | 1024 | 0.1813          | 0.9564   |
| 0.0003        | 8.5   | 1088 | 0.1982          | 0.9530   |
| 0.0003        | 9.0   | 1152 | 0.2061          | 0.9530   |
| 0.0003        | 9.5   | 1216 | 0.2035          | 0.9530   |
| 0.0002        | 10.0  | 1280 | 0.2063          | 0.9530   |
| 0.0002        | 10.5  | 1344 | 0.2074          | 0.9530   |
| 0.0002        | 11.0  | 1408 | 0.2072          | 0.9530   |
| 0.0002        | 11.5  | 1472 | 0.2093          | 0.9530   |
| 0.0002        | 12.0  | 1536 | 0.2017          | 0.9564   |
| 0.0002        | 12.5  | 1600 | 0.2109          | 0.9530   |
| 0.0001        | 13.0  | 1664 | 0.2203          | 0.9530   |
| 0.0001        | 13.5  | 1728 | 0.2152          | 0.9530   |
| 0.0001        | 14.0  | 1792 | 0.2220          | 0.9530   |
| 0.0001        | 14.5  | 1856 | 0.2251          | 0.9530   |
| 0.0001        | 15.0  | 1920 | 0.2214          | 0.9530   |
| 0.0001        | 15.5  | 1984 | 0.2219          | 0.9530   |
| 0.0001        | 16.0  | 2048 | 0.2219          | 0.9530   |
| 0.0001        | 16.5  | 2112 | 0.2200          | 0.9564   |
| 0.0001        | 17.0  | 2176 | 0.2324          | 0.9530   |
| 0.0001        | 17.5  | 2240 | 0.2330          | 0.9530   |
| 0.0001        | 18.0  | 2304 | 0.2349          | 0.9530   |
| 0.0001        | 18.5  | 2368 | 0.2334          | 0.9530   |
| 0.0001        | 19.0  | 2432 | 0.2365          | 0.9530   |
| 0.0001        | 19.5  | 2496 | 0.2364          | 0.9530   |
| 0.0001        | 20.0  | 2560 | 0.2358          | 0.9530   |
| 0.0001        | 20.5  | 2624 | 0.2362          | 0.9530   |
| 0.0001        | 21.0  | 2688 | 0.2388          | 0.9530   |
| 0.0001        | 21.5  | 2752 | 0.2420          | 0.9530   |
| 0.0001        | 22.0  | 2816 | 0.2401          | 0.9530   |
| 0.0001        | 22.5  | 2880 | 0.2433          | 0.9530   |
| 0.0           | 23.0  | 2944 | 0.2398          | 0.9564   |
| 0.0           | 23.5  | 3008 | 0.2445          | 0.9530   |
| 0.0           | 24.0  | 3072 | 0.2462          | 0.9530   |
| 0.0           | 24.5  | 3136 | 0.2460          | 0.9530   |
| 0.0           | 25.0  | 3200 | 0.2460          | 0.9530   |
| 0.0           | 25.5  | 3264 | 0.2494          | 0.9530   |
| 0.0           | 26.0  | 3328 | 0.2527          | 0.9497   |
| 0.0           | 26.5  | 3392 | 0.2507          | 0.9530   |
| 0.0           | 27.0  | 3456 | 0.2503          | 0.9564   |
| 0.0           | 27.5  | 3520 | 0.2570          | 0.9530   |
| 0.0           | 28.0  | 3584 | 0.2545          | 0.9530   |
| 0.0           | 28.5  | 3648 | 0.2562          | 0.9530   |
| 0.0           | 29.0  | 3712 | 0.2565          | 0.9530   |
| 0.0           | 29.5  | 3776 | 0.2562          | 0.9530   |
| 0.0           | 30.0  | 3840 | 0.2563          | 0.9530   |


### 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