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# convnextv2-base-1k-224_rice-leaf-disease-augmented-v4_v5_pft

This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6774
- Accuracy: 0.7819

## 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: 0.0003
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0691        | 0.5   | 64   | 2.0083          | 0.3523   |
| 1.9566        | 1.0   | 128  | 1.8732          | 0.5201   |
| 1.7715        | 1.5   | 192  | 1.6903          | 0.5638   |
| 1.5752        | 2.0   | 256  | 1.5040          | 0.6074   |
| 1.4088        | 2.5   | 320  | 1.3569          | 0.6208   |
| 1.2927        | 3.0   | 384  | 1.2600          | 0.6309   |
| 1.2173        | 3.5   | 448  | 1.1948          | 0.6577   |
| 1.1515        | 4.0   | 512  | 1.1464          | 0.6644   |
| 1.1183        | 4.5   | 576  | 1.1160          | 0.6711   |
| 1.0893        | 5.0   | 640  | 1.1001          | 0.6879   |
| 1.0792        | 5.5   | 704  | 1.0898          | 0.6913   |
| 1.0627        | 6.0   | 768  | 1.0831          | 0.6846   |
| 1.0714        | 6.5   | 832  | 1.0817          | 0.6846   |
| 1.0459        | 7.0   | 896  | 1.0483          | 0.6913   |
| 1.0282        | 7.5   | 960  | 1.0047          | 0.6980   |
| 0.9605        | 8.0   | 1024 | 0.9774          | 0.7081   |
| 0.9405        | 8.5   | 1088 | 0.9489          | 0.7114   |
| 0.9316        | 9.0   | 1152 | 0.9353          | 0.7148   |
| 0.9174        | 9.5   | 1216 | 0.9208          | 0.7181   |
| 0.8924        | 10.0  | 1280 | 0.9137          | 0.7215   |
| 0.9009        | 10.5  | 1344 | 0.9101          | 0.7282   |
| 0.8844        | 11.0  | 1408 | 0.9092          | 0.7248   |
| 0.8873        | 11.5  | 1472 | 0.9076          | 0.7215   |
| 0.8751        | 12.0  | 1536 | 0.8721          | 0.7383   |
| 0.8553        | 12.5  | 1600 | 0.8617          | 0.7248   |
| 0.8265        | 13.0  | 1664 | 0.8428          | 0.7416   |
| 0.8133        | 13.5  | 1728 | 0.8302          | 0.7416   |
| 0.808         | 14.0  | 1792 | 0.8232          | 0.7483   |
| 0.7915        | 14.5  | 1856 | 0.8187          | 0.7450   |
| 0.7975        | 15.0  | 1920 | 0.8157          | 0.7450   |
| 0.7765        | 15.5  | 1984 | 0.8143          | 0.7450   |
| 0.8017        | 16.0  | 2048 | 0.8142          | 0.7450   |
| 0.793         | 16.5  | 2112 | 0.7970          | 0.7584   |
| 0.7567        | 17.0  | 2176 | 0.7901          | 0.7550   |
| 0.7576        | 17.5  | 2240 | 0.7785          | 0.7483   |
| 0.7377        | 18.0  | 2304 | 0.7651          | 0.7651   |
| 0.7311        | 18.5  | 2368 | 0.7588          | 0.7651   |
| 0.7276        | 19.0  | 2432 | 0.7566          | 0.7651   |
| 0.7237        | 19.5  | 2496 | 0.7567          | 0.7651   |
| 0.7171        | 20.0  | 2560 | 0.7534          | 0.7685   |
| 0.7158        | 20.5  | 2624 | 0.7529          | 0.7685   |
| 0.7188        | 21.0  | 2688 | 0.7486          | 0.7651   |
| 0.7112        | 21.5  | 2752 | 0.7340          | 0.7752   |
| 0.6912        | 22.0  | 2816 | 0.7297          | 0.7752   |
| 0.6784        | 22.5  | 2880 | 0.7229          | 0.7785   |
| 0.6868        | 23.0  | 2944 | 0.7152          | 0.7752   |
| 0.6701        | 23.5  | 3008 | 0.7132          | 0.7819   |
| 0.6718        | 24.0  | 3072 | 0.7111          | 0.7752   |
| 0.671         | 24.5  | 3136 | 0.7105          | 0.7785   |
| 0.6609        | 25.0  | 3200 | 0.7097          | 0.7785   |
| 0.6722        | 25.5  | 3264 | 0.7066          | 0.7785   |
| 0.6526        | 26.0  | 3328 | 0.6959          | 0.7785   |
| 0.6448        | 26.5  | 3392 | 0.6920          | 0.7919   |
| 0.6493        | 27.0  | 3456 | 0.6903          | 0.7785   |
| 0.6394        | 27.5  | 3520 | 0.6816          | 0.7785   |
| 0.6274        | 28.0  | 3584 | 0.6819          | 0.7819   |
| 0.6198        | 28.5  | 3648 | 0.6784          | 0.7819   |
| 0.632         | 29.0  | 3712 | 0.6778          | 0.7819   |
| 0.634         | 29.5  | 3776 | 0.6776          | 0.7819   |
| 0.612         | 30.0  | 3840 | 0.6774          | 0.7819   |


### 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