---
library_name: transformers
license: apache-2.0
base_model: WinKawaks/vit-tiny-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-tiny-patch16-224_rice-leaf-disease-augmented-v4_fft
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-tiny-patch16-224_rice-leaf-disease-augmented-v4_fft

This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3674
- Accuracy: 0.9262

## 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 |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.0564        | 0.5   | 64   | 0.4899   | 1.4541          |
| 1.0767        | 1.0   | 128  | 0.7651   | 0.6909          |
| 0.4917        | 1.5   | 192  | 0.8322   | 0.4307          |
| 0.285         | 2.0   | 256  | 0.9027   | 0.2932          |
| 0.0902        | 2.5   | 320  | 0.8993   | 0.3134          |
| 0.0588        | 3.0   | 384  | 0.9161   | 0.3076          |
| 0.0155        | 3.5   | 448  | 0.9396   | 0.2627          |
| 0.0066        | 4.0   | 512  | 0.9295   | 0.2992          |
| 0.0017        | 4.5   | 576  | 0.9228   | 0.2936          |
| 0.0009        | 5.0   | 640  | 0.9228   | 0.2961          |
| 0.0006        | 5.5   | 704  | 0.9228   | 0.3005          |
| 0.0005        | 6.0   | 768  | 0.9228   | 0.3004          |
| 0.0005        | 6.5   | 832  | 0.9262   | 0.2867          |
| 0.0004        | 7.0   | 896  | 0.9295   | 0.2977          |
| 0.0003        | 7.5   | 960  | 0.9295   | 0.2944          |
| 0.0002        | 8.0   | 1024 | 0.9295   | 0.3074          |
| 0.0002        | 8.5   | 1088 | 0.9329   | 0.3053          |
| 0.0002        | 9.0   | 1152 | 0.9295   | 0.3098          |
| 0.0001        | 9.5   | 1216 | 0.9295   | 0.3102          |
| 0.0001        | 10.0  | 1280 | 0.9262   | 0.3105          |
| 0.0001        | 10.5  | 1344 | 0.9262   | 0.3105          |
| 0.0001        | 11.0  | 1408 | 0.9262   | 0.3202          |
| 0.0001        | 11.5  | 1472 | 0.9295   | 0.3183          |
| 0.0001        | 12.0  | 1536 | 0.9329   | 0.3131          |
| 0.0001        | 12.5  | 1600 | 0.9295   | 0.3157          |
| 0.0001        | 13.0  | 1664 | 0.9228   | 0.3238          |
| 0.0001        | 13.5  | 1728 | 0.9228   | 0.3220          |
| 0.0001        | 14.0  | 1792 | 0.9228   | 0.3266          |
| 0.0001        | 14.5  | 1856 | 0.9228   | 0.3274          |
| 0.0001        | 15.0  | 1920 | 0.9228   | 0.3269          |
| 0.0001        | 15.5  | 1984 | 0.3267   | 0.9262          |
| 0.0001        | 16.0  | 2048 | 0.3298   | 0.9228          |
| 0.0001        | 16.5  | 2112 | 0.3330   | 0.9228          |
| 0.0001        | 17.0  | 2176 | 0.3337   | 0.9228          |
| 0.0001        | 17.5  | 2240 | 0.3337   | 0.9228          |
| 0.0001        | 18.0  | 2304 | 0.3355   | 0.9228          |
| 0.0           | 18.5  | 2368 | 0.3346   | 0.9228          |
| 0.0           | 19.0  | 2432 | 0.3360   | 0.9228          |
| 0.0           | 19.5  | 2496 | 0.3368   | 0.9228          |
| 0.0           | 20.0  | 2560 | 0.3365   | 0.9228          |
| 0.0           | 20.5  | 2624 | 0.3364   | 0.9228          |
| 0.0           | 21.0  | 2688 | 0.3412   | 0.9228          |
| 0.0           | 21.5  | 2752 | 0.3414   | 0.9228          |
| 0.0           | 22.0  | 2816 | 0.3435   | 0.9262          |
| 0.0           | 22.5  | 2880 | 0.3557   | 0.9228          |
| 0.0           | 23.0  | 2944 | 0.3490   | 0.9295          |
| 0.0           | 23.5  | 3008 | 0.3564   | 0.9262          |
| 0.0           | 24.0  | 3072 | 0.3545   | 0.9295          |
| 0.0           | 24.5  | 3136 | 0.3577   | 0.9262          |
| 0.0           | 25.0  | 3200 | 0.3597   | 0.9262          |
| 0.0           | 25.5  | 3264 | 0.3632   | 0.9262          |
| 0.0           | 26.0  | 3328 | 0.3627   | 0.9262          |
| 0.0           | 26.5  | 3392 | 0.3650   | 0.9262          |
| 0.0           | 27.0  | 3456 | 0.3664   | 0.9262          |
| 0.0           | 27.5  | 3520 | 0.3664   | 0.9262          |
| 0.0           | 28.0  | 3584 | 0.3666   | 0.9262          |
| 0.0           | 28.5  | 3648 | 0.3666   | 0.9262          |
| 0.0           | 29.0  | 3712 | 0.3670   | 0.9262          |
| 0.0           | 29.5  | 3776 | 0.3673   | 0.9262          |
| 0.0           | 30.0  | 3840 | 0.3674   | 0.9262          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1