---
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_tl_020125
  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_tl_020125

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: 0.6522
- Accuracy: 0.7885

## 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: 0.0001
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.023         | 1.0   | 250  | 0.406    | 1.7331          |
| 1.4339        | 2.0   | 500  | 0.638    | 1.1983          |
| 1.0891        | 3.0   | 750  | 0.6985   | 0.9888          |
| 0.9387        | 4.0   | 1000 | 0.728    | 0.8833          |
| 0.8519        | 5.0   | 1250 | 0.7455   | 0.8170          |
| 0.7933        | 6.0   | 1500 | 0.7575   | 0.7714          |
| 0.7515        | 7.0   | 1750 | 0.7635   | 0.7390          |
| 0.7208        | 8.0   | 2000 | 0.7695   | 0.7137          |
| 0.6967        | 9.0   | 2250 | 0.774    | 0.6958          |
| 0.6787        | 10.0  | 2500 | 0.7795   | 0.6809          |
| 0.6644        | 11.0  | 2750 | 0.783    | 0.6697          |
| 0.6539        | 12.0  | 3000 | 0.7825   | 0.6619          |
| 0.6463        | 13.0  | 3250 | 0.7875   | 0.6563          |
| 0.6411        | 14.0  | 3500 | 0.789    | 0.6533          |
| 0.6385        | 15.0  | 3750 | 0.7885   | 0.6522          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0