metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224_rice-leaf-disease-augmented-v2_tl
results: []
vit-base-patch16-224_rice-leaf-disease-augmented-v2_tl
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6919
- Accuracy: 0.7679
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 |
|---|---|---|---|---|
| 2.1171 | 1.0 | 63 | 1.8775 | 0.2946 |
| 1.6139 | 2.0 | 126 | 1.3619 | 0.5476 |
| 1.1727 | 3.0 | 189 | 1.1003 | 0.6577 |
| 0.9586 | 4.0 | 252 | 0.9665 | 0.7232 |
| 0.8409 | 5.0 | 315 | 0.8663 | 0.7440 |
| 0.7632 | 6.0 | 378 | 0.8322 | 0.7381 |
| 0.7093 | 7.0 | 441 | 0.8039 | 0.7470 |
| 0.6667 | 8.0 | 504 | 0.7722 | 0.75 |
| 0.6353 | 9.0 | 567 | 0.7477 | 0.7560 |
| 0.6101 | 10.0 | 630 | 0.7304 | 0.7589 |
| 0.5894 | 11.0 | 693 | 0.7229 | 0.7649 |
| 0.5737 | 12.0 | 756 | 0.7130 | 0.7619 |
| 0.5627 | 13.0 | 819 | 0.7033 | 0.7649 |
| 0.5524 | 14.0 | 882 | 0.7009 | 0.7649 |
| 0.5439 | 15.0 | 945 | 0.6945 | 0.7679 |
| 0.5397 | 16.0 | 1008 | 0.6937 | 0.7649 |
| 0.5357 | 17.0 | 1071 | 0.6933 | 0.7679 |
| 0.5337 | 18.0 | 1134 | 0.6919 | 0.7679 |
| 0.5322 | 19.0 | 1197 | 0.6921 | 0.7679 |
| 0.5325 | 20.0 | 1260 | 0.6919 | 0.7679 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0