---
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_tl
  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_tl

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: 0.6919
- Accuracy: 0.7679

## 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: 128
- eval_batch_size: 128
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1171        | 1.0   | 63   | 1.8775          | 0.2946   |
| 1.6139        | 2.0   | 126  | 1.3619          | 0.5476   |
| 1.1727        | 3.0   | 189  | 1.1003          | 0.6577   |
| 0.9586        | 4.0   | 252  | 0.9665          | 0.7232   |
| 0.8409        | 5.0   | 315  | 0.8663          | 0.7440   |
| 0.7632        | 6.0   | 378  | 0.8322          | 0.7381   |
| 0.7093        | 7.0   | 441  | 0.8039          | 0.7470   |
| 0.6667        | 8.0   | 504  | 0.7722          | 0.75     |
| 0.6353        | 9.0   | 567  | 0.7477          | 0.7560   |
| 0.6101        | 10.0  | 630  | 0.7304          | 0.7589   |
| 0.5894        | 11.0  | 693  | 0.7229          | 0.7649   |
| 0.5737        | 12.0  | 756  | 0.7130          | 0.7619   |
| 0.5627        | 13.0  | 819  | 0.7033          | 0.7649   |
| 0.5524        | 14.0  | 882  | 0.7009          | 0.7649   |
| 0.5439        | 15.0  | 945  | 0.6945          | 0.7679   |
| 0.5397        | 16.0  | 1008 | 0.6937          | 0.7649   |
| 0.5357        | 17.0  | 1071 | 0.6933          | 0.7679   |
| 0.5337        | 18.0  | 1134 | 0.6919          | 0.7679   |
| 0.5322        | 19.0  | 1197 | 0.6921          | 0.7679   |
| 0.5325        | 20.0  | 1260 | 0.6919          | 0.7679   |


### Framework versions

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