---
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_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. -->

# beit-base-patch16-224_rice-leaf-disease-augmented-v2_tl

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: 0.4947
- Accuracy: 0.8512

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0747        | 1.0   | 63   | 1.7043          | 0.4435   |
| 1.3282        | 2.0   | 126  | 1.0444          | 0.6845   |
| 0.8626        | 3.0   | 189  | 0.7962          | 0.7470   |
| 0.6929        | 4.0   | 252  | 0.6883          | 0.8125   |
| 0.5935        | 5.0   | 315  | 0.6247          | 0.8214   |
| 0.5427        | 6.0   | 378  | 0.5926          | 0.8244   |
| 0.5002        | 7.0   | 441  | 0.5735          | 0.8452   |
| 0.4704        | 8.0   | 504  | 0.5520          | 0.8482   |
| 0.4521        | 9.0   | 567  | 0.5330          | 0.8363   |
| 0.4311        | 10.0  | 630  | 0.5249          | 0.8512   |
| 0.4096        | 11.0  | 693  | 0.5185          | 0.8512   |
| 0.3999        | 12.0  | 756  | 0.5112          | 0.8542   |
| 0.3918        | 13.0  | 819  | 0.5042          | 0.8512   |
| 0.3862        | 14.0  | 882  | 0.4984          | 0.8542   |
| 0.3784        | 15.0  | 945  | 0.4985          | 0.8512   |
| 0.3733        | 16.0  | 1008 | 0.4967          | 0.8512   |
| 0.3763        | 17.0  | 1071 | 0.4947          | 0.8512   |
| 0.3736        | 18.0  | 1134 | 0.4949          | 0.8512   |
| 0.3718        | 19.0  | 1197 | 0.4948          | 0.8512   |
| 0.3722        | 20.0  | 1260 | 0.4947          | 0.8512   |


### Framework versions

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