---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dinov2-base_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. -->

# dinov2-base_rice-leaf-disease-augmented-v2_fft

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6772
- Accuracy: 0.9018

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8654        | 1.0   | 125  | 0.4470          | 0.8661   |
| 0.2009        | 2.0   | 250  | 0.5260          | 0.8631   |
| 0.1148        | 3.0   | 375  | 0.6247          | 0.8690   |
| 0.0412        | 4.0   | 500  | 0.5468          | 0.8988   |
| 0.0052        | 5.0   | 625  | 0.5418          | 0.9018   |
| 0.0001        | 6.0   | 750  | 0.5245          | 0.9077   |
| 0.0863        | 7.0   | 875  | 0.6622          | 0.8571   |
| 0.059         | 8.0   | 1000 | 0.6755          | 0.8869   |
| 0.0153        | 9.0   | 1125 | 0.6671          | 0.9048   |
| 0.0014        | 10.0  | 1250 | 0.6834          | 0.8988   |
| 0.0           | 11.0  | 1375 | 0.6805          | 0.9018   |
| 0.0           | 12.0  | 1500 | 0.6765          | 0.9048   |
| 0.0           | 13.0  | 1625 | 0.6773          | 0.9018   |
| 0.0           | 14.0  | 1750 | 0.6771          | 0.9018   |
| 0.0           | 15.0  | 1875 | 0.6772          | 0.9018   |


### Framework versions

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