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---
library_name: transformers
license: apache-2.0
base_model: google/vit-hybrid-base-bit-384
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-hybrid-base-bit-384_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. -->
# vit-hybrid-base-bit-384_rice-leaf-disease-augmented-v2_fft
This model is a fine-tuned version of [google/vit-hybrid-base-bit-384](https://huggingface.co/google/vit-hybrid-base-bit-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3756
- Accuracy: 0.9286
## 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_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.203 | 1.0 | 250 | 0.4459 | 0.8512 |
| 0.1159 | 2.0 | 500 | 0.3121 | 0.9077 |
| 0.0136 | 3.0 | 750 | 0.3433 | 0.9226 |
| 0.001 | 4.0 | 1000 | 0.3377 | 0.9226 |
| 0.0003 | 5.0 | 1250 | 0.3365 | 0.9226 |
| 0.0002 | 6.0 | 1500 | 0.3366 | 0.9286 |
| 0.0002 | 7.0 | 1750 | 0.3432 | 0.9286 |
| 0.0001 | 8.0 | 2000 | 0.3478 | 0.9286 |
| 0.0001 | 9.0 | 2250 | 0.3530 | 0.9286 |
| 0.0001 | 10.0 | 2500 | 0.3543 | 0.9286 |
| 0.0001 | 11.0 | 2750 | 0.3592 | 0.9286 |
| 0.0 | 12.0 | 3000 | 0.3698 | 0.9286 |
| 0.0 | 13.0 | 3250 | 0.3730 | 0.9286 |
| 0.0 | 14.0 | 3500 | 0.3750 | 0.9286 |
| 0.0 | 15.0 | 3750 | 0.3756 | 0.9286 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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