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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_tl_020125
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_tl_020125
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: 0.1132
- Accuracy: 0.966
## 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: 0.001
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.1218 | 1.0 | 250 | 0.825 | 0.5307 |
| 0.4069 | 2.0 | 500 | 0.885 | 0.3582 |
| 0.2746 | 3.0 | 750 | 0.92 | 0.2464 |
| 0.2157 | 4.0 | 1000 | 0.9315 | 0.2224 |
| 0.1779 | 5.0 | 1250 | 0.949 | 0.1753 |
| 0.1539 | 6.0 | 1500 | 0.942 | 0.1718 |
| 0.1361 | 7.0 | 1750 | 0.9515 | 0.1603 |
| 0.1271 | 8.0 | 2000 | 0.958 | 0.1448 |
| 0.1114 | 9.0 | 2250 | 0.951 | 0.1444 |
| 0.1023 | 10.0 | 2500 | 0.959 | 0.1309 |
| 0.0968 | 11.0 | 2750 | 0.9625 | 0.1240 |
| 0.0911 | 12.0 | 3000 | 0.9645 | 0.1248 |
| 0.0858 | 13.0 | 3250 | 0.962 | 0.1189 |
| 0.0818 | 14.0 | 3500 | 0.9645 | 0.1136 |
| 0.0789 | 15.0 | 3750 | 0.966 | 0.1132 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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