---
library_name: transformers
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-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. -->

# beit-base-patch16-224_rice-leaf-disease-augmented-v2_fft

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5324
- Accuracy: 0.9137

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6553        | 1.0   | 125  | 0.7916          | 0.7530   |
| 0.481         | 2.0   | 250  | 0.3628          | 0.8810   |
| 0.1631        | 3.0   | 375  | 0.2895          | 0.8988   |
| 0.0609        | 4.0   | 500  | 0.3242          | 0.9167   |
| 0.0293        | 5.0   | 625  | 0.3503          | 0.9196   |
| 0.0223        | 6.0   | 750  | 0.3411          | 0.9226   |
| 0.0302        | 7.0   | 875  | 0.3786          | 0.9226   |
| 0.014         | 8.0   | 1000 | 0.4169          | 0.9256   |
| 0.0069        | 9.0   | 1125 | 0.4648          | 0.9137   |
| 0.006         | 10.0  | 1250 | 0.4697          | 0.9137   |
| 0.0053        | 11.0  | 1375 | 0.5192          | 0.8958   |
| 0.0093        | 12.0  | 1500 | 0.5058          | 0.9048   |
| 0.0069        | 13.0  | 1625 | 0.5486          | 0.9077   |
| 0.005         | 14.0  | 1750 | 0.5252          | 0.9167   |
| 0.004         | 15.0  | 1875 | 0.5324          | 0.9137   |


### Framework versions

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