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# convnextv2-femto-1k-224_rice-leaf-disease-augmented-v4_fft

This model is a fine-tuned version of [facebook/convnextv2-femto-1k-224](https://huggingface.co/facebook/convnextv2-femto-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2660
- Accuracy: 0.9430

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.0082        | 0.5   | 64   | 0.5268   | 1.6771          |
| 1.2603        | 1.0   | 128  | 0.8020   | 0.8211          |
| 0.6327        | 1.5   | 192  | 0.8389   | 0.4743          |
| 0.3835        | 2.0   | 256  | 0.9128   | 0.3028          |
| 0.2059        | 2.5   | 320  | 0.9027   | 0.2902          |
| 0.1242        | 3.0   | 384  | 0.9228   | 0.2034          |
| 0.048         | 3.5   | 448  | 0.9027   | 0.2552          |
| 0.0306        | 4.0   | 512  | 0.9295   | 0.1963          |
| 0.0103        | 4.5   | 576  | 0.9329   | 0.2063          |
| 0.0068        | 5.0   | 640  | 0.9530   | 0.1742          |
| 0.0025        | 5.5   | 704  | 0.9430   | 0.1839          |
| 0.002         | 6.0   | 768  | 0.9463   | 0.1890          |
| 0.0019        | 6.5   | 832  | 0.9228   | 0.3096          |
| 0.0064        | 7.0   | 896  | 0.9262   | 0.2344          |
| 0.0049        | 7.5   | 960  | 0.9228   | 0.2725          |
| 0.003         | 8.0   | 1024 | 0.9463   | 0.2240          |
| 0.0005        | 8.5   | 1088 | 0.9430   | 0.2407          |
| 0.0003        | 9.0   | 1152 | 0.9262   | 0.2760          |
| 0.0002        | 9.5   | 1216 | 0.9463   | 0.2308          |
| 0.0001        | 10.0  | 1280 | 0.9497   | 0.2359          |
| 0.0001        | 10.5  | 1344 | 0.9497   | 0.2367          |
| 0.0001        | 11.0  | 1408 | 0.9497   | 0.2378          |
| 0.0001        | 11.5  | 1472 | 0.9497   | 0.2422          |
| 0.0001        | 12.0  | 1536 | 0.9430   | 0.2403          |
| 0.0001        | 12.5  | 1600 | 0.9463   | 0.2343          |
| 0.0001        | 13.0  | 1664 | 0.9396   | 0.2461          |
| 0.0001        | 13.5  | 1728 | 0.9497   | 0.2434          |
| 0.0001        | 14.0  | 1792 | 0.9430   | 0.2426          |
| 0.0001        | 14.5  | 1856 | 0.9463   | 0.2433          |
| 0.0001        | 15.0  | 1920 | 0.9463   | 0.2432          |
| 0.0001        | 15.5  | 1984 | 0.2458   | 0.9396          |
| 0.0001        | 16.0  | 2048 | 0.2474   | 0.9396          |
| 0.0           | 16.5  | 2112 | 0.2436   | 0.9497          |
| 0.0           | 17.0  | 2176 | 0.2508   | 0.9396          |
| 0.0           | 17.5  | 2240 | 0.2490   | 0.9362          |
| 0.0           | 18.0  | 2304 | 0.2485   | 0.9463          |
| 0.0           | 18.5  | 2368 | 0.2513   | 0.9362          |
| 0.0           | 19.0  | 2432 | 0.2480   | 0.9396          |
| 0.0           | 19.5  | 2496 | 0.2485   | 0.9430          |
| 0.0           | 20.0  | 2560 | 0.2483   | 0.9396          |
| 0.0           | 20.5  | 2624 | 0.2484   | 0.9396          |
| 0.0           | 21.0  | 2688 | 0.2509   | 0.9362          |
| 0.0           | 21.5  | 2752 | 0.2551   | 0.9463          |
| 0.0           | 22.0  | 2816 | 0.2562   | 0.9362          |
| 0.0           | 22.5  | 2880 | 0.2577   | 0.9362          |
| 0.0           | 23.0  | 2944 | 0.2586   | 0.9497          |
| 0.0           | 23.5  | 3008 | 0.2643   | 0.9430          |
| 0.0           | 24.0  | 3072 | 0.2615   | 0.9430          |
| 0.0           | 24.5  | 3136 | 0.2633   | 0.9430          |
| 0.0           | 25.0  | 3200 | 0.2642   | 0.9396          |
| 0.0           | 25.5  | 3264 | 0.2615   | 0.9430          |
| 0.0           | 26.0  | 3328 | 0.2667   | 0.9430          |
| 0.0           | 26.5  | 3392 | 0.2650   | 0.9430          |
| 0.0           | 27.0  | 3456 | 0.2658   | 0.9396          |
| 0.0           | 27.5  | 3520 | 0.2651   | 0.9396          |
| 0.0           | 28.0  | 3584 | 0.2656   | 0.9396          |
| 0.0           | 28.5  | 3648 | 0.2660   | 0.9430          |
| 0.0           | 29.0  | 3712 | 0.2663   | 0.9430          |
| 0.0           | 29.5  | 3776 | 0.2665   | 0.9430          |
| 0.0           | 30.0  | 3840 | 0.2660   | 0.9430          |


### 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