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# efficientnet-b0_rice-leaf-disease-augmented-v4_fft

This model is a fine-tuned version of [google/efficientnet-b0](https://huggingface.co/google/efficientnet-b0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3800
- Accuracy: 0.9128

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.0658        | 0.5   | 64   | 0.2450   | 1.9987          |
| 1.9318        | 1.0   | 128  | 0.4262   | 1.7967          |
| 1.6451        | 1.5   | 192  | 0.5604   | 1.4543          |
| 1.2851        | 2.0   | 256  | 0.6846   | 1.0678          |
| 0.9017        | 2.5   | 320  | 0.7617   | 0.8011          |
| 0.6891        | 3.0   | 384  | 0.8054   | 0.6284          |
| 0.5118        | 3.5   | 448  | 0.8020   | 0.6124          |
| 0.4458        | 4.0   | 512  | 0.8121   | 0.6052          |
| 0.356         | 4.5   | 576  | 0.8289   | 0.5032          |
| 0.3255        | 5.0   | 640  | 0.8523   | 0.4429          |
| 0.294         | 5.5   | 704  | 0.8490   | 0.4829          |
| 0.2856        | 6.0   | 768  | 0.8389   | 0.4863          |
| 0.289         | 6.5   | 832  | 0.8523   | 0.4306          |
| 0.2357        | 7.0   | 896  | 0.8591   | 0.4408          |
| 0.183         | 7.5   | 960  | 0.8691   | 0.3810          |
| 0.1446        | 8.0   | 1024 | 0.8624   | 0.3680          |
| 0.1094        | 8.5   | 1088 | 0.8826   | 0.3557          |
| 0.102         | 9.0   | 1152 | 0.8826   | 0.3555          |
| 0.0752        | 9.5   | 1216 | 0.8826   | 0.3514          |
| 0.0828        | 10.0  | 1280 | 0.8691   | 0.4008          |
| 0.0758        | 10.5  | 1344 | 0.8792   | 0.3509          |
| 0.0699        | 11.0  | 1408 | 0.8893   | 0.3737          |
| 0.059         | 11.5  | 1472 | 0.8859   | 0.3488          |
| 0.0504        | 12.0  | 1536 | 0.9027   | 0.3544          |
| 0.0381        | 12.5  | 1600 | 0.8926   | 0.3867          |
| 0.0293        | 13.0  | 1664 | 0.8893   | 0.3593          |
| 0.0257        | 13.5  | 1728 | 0.8993   | 0.3230          |
| 0.0258        | 14.0  | 1792 | 0.8893   | 0.4092          |
| 0.0249        | 14.5  | 1856 | 0.8859   | 0.4291          |
| 0.0187        | 15.0  | 1920 | 0.8993   | 0.3305          |
| 0.0226        | 15.5  | 1984 | 0.3599   | 0.8893          |
| 0.0222        | 16.0  | 2048 | 0.3777   | 0.8993          |
| 0.0151        | 16.5  | 2112 | 0.3345   | 0.9060          |
| 0.0181        | 17.0  | 2176 | 0.3589   | 0.8960          |
| 0.0144        | 17.5  | 2240 | 0.3440   | 0.8960          |
| 0.0117        | 18.0  | 2304 | 0.4319   | 0.9027          |
| 0.013         | 18.5  | 2368 | 0.3972   | 0.8960          |
| 0.0111        | 19.0  | 2432 | 0.3337   | 0.8926          |
| 0.0106        | 19.5  | 2496 | 0.3284   | 0.9027          |
| 0.0114        | 20.0  | 2560 | 0.3483   | 0.9027          |
| 0.0111        | 20.5  | 2624 | 0.3425   | 0.8993          |
| 0.0106        | 21.0  | 2688 | 0.3333   | 0.8993          |
| 0.011         | 21.5  | 2752 | 0.3795   | 0.9027          |
| 0.0106        | 22.0  | 2816 | 0.4228   | 0.9027          |
| 0.0075        | 22.5  | 2880 | 0.4410   | 0.8859          |
| 0.0075        | 23.0  | 2944 | 0.3461   | 0.8993          |
| 0.0057        | 23.5  | 3008 | 0.3992   | 0.9027          |
| 0.0058        | 24.0  | 3072 | 0.3577   | 0.9060          |
| 0.0041        | 24.5  | 3136 | 0.4393   | 0.8993          |
| 0.0042        | 25.0  | 3200 | 0.3816   | 0.8960          |
| 0.0045        | 25.5  | 3264 | 0.4059   | 0.9027          |
| 0.0033        | 26.0  | 3328 | 0.4299   | 0.8960          |
| 0.0038        | 26.5  | 3392 | 0.4605   | 0.8993          |
| 0.004         | 27.0  | 3456 | 0.3973   | 0.9027          |
| 0.0033        | 27.5  | 3520 | 0.4126   | 0.9094          |
| 0.0049        | 28.0  | 3584 | 0.3783   | 0.9128          |
| 0.0027        | 28.5  | 3648 | 0.3632   | 0.9094          |
| 0.0033        | 29.0  | 3712 | 0.4586   | 0.9027          |
| 0.0039        | 29.5  | 3776 | 0.4505   | 0.8960          |
| 0.0037        | 30.0  | 3840 | 0.3800   | 0.9128          |


### 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