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---
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
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