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# efficientnet-b2_rice-leaf-disease-augmented-v4_v5_fft

This model is a fine-tuned version of [google/efficientnet-b2](https://huggingface.co/google/efficientnet-b2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2236
- Accuracy: 0.9362

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0775        | 0.5   | 64   | 2.0200          | 0.2282   |
| 1.9215        | 1.0   | 128  | 1.7530          | 0.5336   |
| 1.5941        | 1.5   | 192  | 1.3576          | 0.6309   |
| 1.1312        | 2.0   | 256  | 0.8490          | 0.7517   |
| 0.6799        | 2.5   | 320  | 0.5743          | 0.8221   |
| 0.4743        | 3.0   | 384  | 0.4281          | 0.8624   |
| 0.2937        | 3.5   | 448  | 0.3946          | 0.8893   |
| 0.2342        | 4.0   | 512  | 0.3713          | 0.8758   |
| 0.1563        | 4.5   | 576  | 0.3339          | 0.8893   |
| 0.1296        | 5.0   | 640  | 0.2886          | 0.9128   |
| 0.1026        | 5.5   | 704  | 0.3032          | 0.8926   |
| 0.1009        | 6.0   | 768  | 0.2951          | 0.8893   |
| 0.0956        | 6.5   | 832  | 0.2795          | 0.9128   |
| 0.0817        | 7.0   | 896  | 0.3031          | 0.9094   |
| 0.0591        | 7.5   | 960  | 0.2778          | 0.9195   |
| 0.0444        | 8.0   | 1024 | 0.2435          | 0.9060   |
| 0.0268        | 8.5   | 1088 | 0.2506          | 0.9228   |
| 0.0198        | 9.0   | 1152 | 0.2692          | 0.8993   |
| 0.0139        | 9.5   | 1216 | 0.2384          | 0.9195   |
| 0.0164        | 10.0  | 1280 | 0.2712          | 0.9195   |
| 0.0118        | 10.5  | 1344 | 0.2868          | 0.9128   |
| 0.0139        | 11.0  | 1408 | 0.2262          | 0.9295   |
| 0.0122        | 11.5  | 1472 | 0.2492          | 0.9128   |
| 0.0132        | 12.0  | 1536 | 0.2751          | 0.9128   |
| 0.0084        | 12.5  | 1600 | 0.3184          | 0.8993   |
| 0.0082        | 13.0  | 1664 | 0.2596          | 0.9228   |
| 0.0093        | 13.5  | 1728 | 0.2636          | 0.9228   |
| 0.0059        | 14.0  | 1792 | 0.2501          | 0.9262   |
| 0.0060        | 14.5  | 1856 | 0.3249          | 0.9027   |
| 0.0036        | 15.0  | 1920 | 0.2584          | 0.9228   |
| 0.0051        | 15.5  | 1984 | 0.2501          | 0.9161   |
| 0.0049        | 16.0  | 2048 | 0.2698          | 0.9228   |
| 0.0042        | 16.5  | 2112 | 0.2403          | 0.9262   |
| 0.0054        | 17.0  | 2176 | 0.2536          | 0.9262   |
| 0.0056        | 17.5  | 2240 | 0.2506          | 0.9228   |
| 0.0031        | 18.0  | 2304 | 0.3199          | 0.9027   |
| 0.0038        | 18.5  | 2368 | 0.3303          | 0.9228   |
| 0.0029        | 19.0  | 2432 | 0.2250          | 0.9295   |
| 0.0024        | 19.5  | 2496 | 0.2577          | 0.9161   |
| 0.0023        | 20.0  | 2560 | 0.2365          | 0.9396   |
| 0.0026        | 20.5  | 2624 | 0.2501          | 0.9295   |
| 0.0034        | 21.0  | 2688 | 0.2283          | 0.9262   |
| 0.0034        | 21.5  | 2752 | 0.2608          | 0.9195   |
| 0.0045        | 22.0  | 2816 | 0.3040          | 0.9094   |
| 0.0023        | 22.5  | 2880 | 0.2782          | 0.9228   |
| 0.0026        | 23.0  | 2944 | 0.2520          | 0.9161   |
| 0.0015        | 23.5  | 3008 | 0.2440          | 0.9228   |
| 0.0015        | 24.0  | 3072 | 0.2341          | 0.9362   |
| 0.0019        | 24.5  | 3136 | 0.2779          | 0.9161   |
| 0.0018        | 25.0  | 3200 | 0.2662          | 0.9362   |
| 0.0016        | 25.5  | 3264 | 0.2244          | 0.9362   |
| 0.0014        | 26.0  | 3328 | 0.3105          | 0.9161   |
| 0.0016        | 26.5  | 3392 | 0.2696          | 0.9195   |
| 0.0022        | 27.0  | 3456 | 0.2696          | 0.9262   |
| 0.0012        | 27.5  | 3520 | 0.2382          | 0.9362   |
| 0.0019        | 28.0  | 3584 | 0.2430          | 0.9329   |
| 0.0010        | 28.5  | 3648 | 0.2321          | 0.9396   |
| 0.0010        | 29.0  | 3712 | 0.2566          | 0.9161   |
| 0.0017        | 29.5  | 3776 | 0.2965          | 0.9295   |
| 0.0013        | 30.0  | 3840 | 0.2236          | 0.9362   |


### 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