---
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-v4_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. -->

# dinov2-base_rice-leaf-disease-augmented-v4_tl

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: 0.2961
- Accuracy: 0.9060

## 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: 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_steps: 256
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.1181        | 0.5   | 64   | 0.3658   | 1.7085          |
| 1.3815        | 1.0   | 128  | 0.7047   | 1.0554          |
| 0.8981        | 1.5   | 192  | 0.7785   | 0.7380          |
| 0.6515        | 2.0   | 256  | 0.7987   | 0.5983          |
| 0.5233        | 2.5   | 320  | 0.8255   | 0.5212          |
| 0.4535        | 3.0   | 384  | 0.8356   | 0.4803          |
| 0.3959        | 3.5   | 448  | 0.8557   | 0.4428          |
| 0.3614        | 4.0   | 512  | 0.8725   | 0.4040          |
| 0.3391        | 4.5   | 576  | 0.8691   | 0.4082          |
| 0.318         | 5.0   | 640  | 0.3749   | 0.8859          |
| 0.3134        | 5.5   | 704  | 0.3922   | 0.8758          |
| 0.3025        | 6.0   | 768  | 0.3802   | 0.8826          |
| 0.3098        | 6.5   | 832  | 0.3856   | 0.8725          |
| 0.2986        | 7.0   | 896  | 0.3666   | 0.8859          |
| 0.2856        | 7.5   | 960  | 0.3525   | 0.8826          |
| 0.2549        | 8.0   | 1024 | 0.3327   | 0.8725          |
| 0.24          | 8.5   | 1088 | 0.3428   | 0.9027          |
| 0.2422        | 9.0   | 1152 | 0.3304   | 0.8993          |
| 0.2178        | 9.5   | 1216 | 0.3238   | 0.9027          |
| 0.2297        | 10.0  | 1280 | 0.3273   | 0.9027          |
| 0.2176        | 10.5  | 1344 | 0.3285   | 0.9027          |
| 0.2236        | 11.0  | 1408 | 0.3411   | 0.8792          |
| 0.2198        | 11.5  | 1472 | 0.3342   | 0.8893          |
| 0.2056        | 12.0  | 1536 | 0.3108   | 0.9060          |
| 0.1915        | 12.5  | 1600 | 0.2995   | 0.8993          |
| 0.1911        | 13.0  | 1664 | 0.3058   | 0.9027          |
| 0.1787        | 13.5  | 1728 | 0.2928   | 0.9128          |
| 0.1776        | 14.0  | 1792 | 0.2979   | 0.9060          |
| 0.1724        | 14.5  | 1856 | 0.2966   | 0.9060          |
| 0.168         | 15.0  | 1920 | 0.2961   | 0.9060          |


### Framework versions

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