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---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-base-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnext-base-224_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. -->
# convnext-base-224_rice-leaf-disease-augmented-v2_fft
This model is a fine-tuned version of [facebook/convnext-base-224](https://huggingface.co/facebook/convnext-base-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3334
- Accuracy: 0.8929
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9755 | 1.0 | 125 | 1.7906 | 0.5119 |
| 1.3671 | 2.0 | 250 | 1.0186 | 0.75 |
| 0.7289 | 3.0 | 375 | 0.6316 | 0.8185 |
| 0.4637 | 4.0 | 500 | 0.5039 | 0.8482 |
| 0.3583 | 5.0 | 625 | 0.4573 | 0.8571 |
| 0.3262 | 6.0 | 750 | 0.4528 | 0.8631 |
| 0.2609 | 7.0 | 875 | 0.3666 | 0.8780 |
| 0.1505 | 8.0 | 1000 | 0.3273 | 0.8899 |
| 0.0925 | 9.0 | 1125 | 0.3147 | 0.8869 |
| 0.0696 | 10.0 | 1250 | 0.3147 | 0.8839 |
| 0.0616 | 11.0 | 1375 | 0.3084 | 0.8929 |
| 0.0335 | 12.0 | 1500 | 0.3218 | 0.8929 |
| 0.0151 | 13.0 | 1625 | 0.3257 | 0.8929 |
| 0.0096 | 14.0 | 1750 | 0.3379 | 0.8929 |
| 0.0085 | 15.0 | 1875 | 0.3334 | 0.8929 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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