---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224_rice-leaf-disease-augmented-v2_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-base-patch16-224_rice-leaf-disease-augmented-v2_fft

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3621
- Accuracy: 0.9226

## 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_ratio: 0.1
- num_epochs: 19
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9482        | 1.0   | 125  | 1.5012          | 0.5685   |
| 0.9894        | 2.0   | 250  | 0.6444          | 0.7976   |
| 0.3321        | 3.0   | 375  | 0.3859          | 0.8958   |
| 0.1115        | 4.0   | 500  | 0.3081          | 0.9107   |
| 0.0387        | 5.0   | 625  | 0.2980          | 0.9137   |
| 0.0204        | 6.0   | 750  | 0.2936          | 0.9137   |
| 0.0169        | 7.0   | 875  | 0.2953          | 0.9196   |
| 0.0078        | 8.0   | 1000 | 0.3067          | 0.9226   |
| 0.0034        | 9.0   | 1125 | 0.3087          | 0.9286   |
| 0.0025        | 10.0  | 1250 | 0.3139          | 0.9196   |
| 0.0023        | 11.0  | 1375 | 0.3142          | 0.9196   |
| 0.0019        | 12.0  | 1500 | 0.3288          | 0.9196   |
| 0.0013        | 13.0  | 1625 | 0.3359          | 0.9196   |
| 0.001         | 14.0  | 1750 | 0.3413          | 0.9226   |
| 0.0009        | 15.0  | 1875 | 0.3425          | 0.9226   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0