---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224_rice-leaf-disease-augmented_fft_012825
  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. -->

# swin-base-patch4-window7-224_rice-leaf-disease-augmented_fft_012825

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0472
- Accuracy: 0.988

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

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.5476        | 1.0   | 250  | 0.789    | 0.5917          |
| 0.3353        | 2.0   | 500  | 0.9575   | 0.1408          |
| 0.0827        | 3.0   | 750  | 0.985    | 0.0427          |
| 0.027         | 4.0   | 1000 | 0.9885   | 0.0344          |
| 0.0095        | 5.0   | 1250 | 0.9925   | 0.0188          |
| 0.0076        | 6.0   | 1500 | 0.995    | 0.0119          |
| 0.003         | 7.0   | 1750 | 0.9955   | 0.0090          |
| 0.0023        | 8.0   | 2000 | 0.9955   | 0.0163          |
| 0.0012        | 9.0   | 2250 | 0.992    | 0.0218          |
| 0.0017        | 10.0  | 2500 | 0.996    | 0.0100          |
| 0.0044        | 11.0  | 2750 | 0.9955   | 0.0236          |
| 0.0048        | 12.0  | 3000 | 0.9925   | 0.0249          |
| 0.0023        | 13.0  | 3250 | 0.9955   | 0.0182          |
| 0.0032        | 14.0  | 3500 | 0.994    | 0.0198          |
| 0.0017        | 15.0  | 3750 | 0.988    | 0.0472          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0