---
library_name: transformers
license: apache-2.0
base_model: facebook/convnextv2-base-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnextv2-base-1k-224_rice-leaf-disease-augmented-v4_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. -->

# convnextv2-base-1k-224_rice-leaf-disease-augmented-v4_fft

This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4315
- Accuracy: 0.9295

## 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: 32
- eval_batch_size: 32
- 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: 512
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9643        | 0.5   | 128  | 1.7264          | 0.6040   |
| 1.2673        | 1.0   | 256  | 0.7987          | 0.8490   |
| 0.5214        | 1.5   | 384  | 0.3728          | 0.9094   |
| 0.2476        | 2.0   | 512  | 0.4170          | 0.8792   |
| 0.104         | 2.5   | 640  | 0.2676          | 0.9262   |
| 0.0573        | 3.0   | 768  | 0.2642          | 0.9262   |
| 0.0262        | 3.5   | 896  | 0.3739          | 0.9228   |
| 0.0171        | 4.0   | 1024 | 0.3519          | 0.9362   |
| 0.0032        | 4.5   | 1152 | 0.3476          | 0.9295   |
| 0.0011        | 5.0   | 1280 | 0.3547          | 0.9362   |
| 0.0008        | 5.5   | 1408 | 0.3541          | 0.9329   |
| 0.0008        | 6.0   | 1536 | 0.3556          | 0.9329   |
| 0.0008        | 6.5   | 1664 | 0.3524          | 0.9329   |
| 0.0005        | 7.0   | 1792 | 0.3775          | 0.9329   |
| 0.0004        | 7.5   | 1920 | 0.3850          | 0.9329   |
| 0.0003        | 8.0   | 2048 | 0.3900          | 0.9329   |
| 0.0003        | 8.5   | 2176 | 0.3965          | 0.9295   |
| 0.0002        | 9.0   | 2304 | 0.4000          | 0.9295   |
| 0.0002        | 9.5   | 2432 | 0.4019          | 0.9295   |
| 0.0002        | 10.0  | 2560 | 0.4018          | 0.9295   |
| 0.0002        | 10.5  | 2688 | 0.4021          | 0.9295   |
| 0.0002        | 11.0  | 2816 | 0.4063          | 0.9329   |
| 0.0002        | 11.5  | 2944 | 0.4145          | 0.9295   |
| 0.0001        | 12.0  | 3072 | 0.4184          | 0.9295   |
| 0.0001        | 12.5  | 3200 | 0.4249          | 0.9295   |
| 0.0001        | 13.0  | 3328 | 0.4271          | 0.9295   |
| 0.0001        | 13.5  | 3456 | 0.4304          | 0.9295   |
| 0.0001        | 14.0  | 3584 | 0.4315          | 0.9295   |
| 0.0001        | 14.5  | 3712 | 0.4316          | 0.9295   |
| 0.0001        | 15.0  | 3840 | 0.4315          | 0.9295   |


### Framework versions

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