---
library_name: transformers
license: other
base_model: apple/mobilevit-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilevit-small_rice-leaf-disease-augmented-v4_v5_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. -->

# mobilevit-small_rice-leaf-disease-augmented-v4_v5_fft

This model is a fine-tuned version of [apple/mobilevit-small](https://huggingface.co/apple/mobilevit-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3882
- Accuracy: 0.9362

## 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_steps: 256
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy  |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 2.0678        | 0.5   | 64   | 2.0341          | 0.2617    |
| 1.9896        | 1.0   | 128  | 1.8927          | 0.5067    |
| 1.768         | 1.5   | 192  | 1.5508          | 0.5336    |
| 1.3736        | 2.0   | 256  | 1.0992          | 0.6779    |
| 0.9732        | 2.5   | 320  | 0.7521          | 0.7685    |
| 0.7316        | 3.0   | 384  | 0.6023          | 0.8121    |
| 0.5769        | 3.5   | 448  | 0.5281          | 0.8121    |
| 0.5013        | 4.0   | 512  | 0.4605          | 0.8423    |
| 0.4329        | 4.5   | 576  | 0.4268          | 0.8691    |
| 0.3821        | 5.0   | 640  | 0.3944          | 0.8859    |
| 0.3602        | 5.5   | 704  | 0.3895          | 0.8859    |
| 0.3496        | 6.0   | 768  | 0.3827          | 0.8893    |
| 0.3507        | 6.5   | 832  | 0.3723          | 0.8859    |
| 0.3225        | 7.0   | 896  | 0.3741          | 0.8893    |
| 0.2924        | 7.5   | 960  | 0.3271          | 0.9027    |
| 0.2298        | 8.0   | 1024 | 0.3185          | 0.8993    |
| 0.1888        | 8.5   | 1088 | 0.3093          | 0.9094    |
| 0.1771        | 9.0   | 1152 | 0.2994          | 0.9094    |
| 0.1461        | 9.5   | 1216 | 0.2907          | 0.9128    |
| 0.1496        | 10.0  | 1280 | 0.3046          | 0.9027    |
| 0.1284        | 10.5  | 1344 | 0.2999          | 0.9027    |
| 0.1323        | 11.0  | 1408 | 0.2904          | 0.9060    |
| 0.1291        | 11.5  | 1472 | 0.2939          | 0.9128    |
| 0.1227        | 12.0  | 1536 | 0.2869          | 0.9027    |
| 0.1033        | 12.5  | 1600 | 0.2886          | 0.9128    |
| 0.0856        | 13.0  | 1664 | 0.3137          | 0.9195    |
| 0.077         | 13.5  | 1728 | 0.3066          | 0.9161    |
| 0.0672        | 14.0  | 1792 | 0.3010          | 0.9094    |
| 0.0601        | 14.5  | 1856 | 0.3260          | 0.9128    |
| 0.0469        | 15.0  | 1920 | 0.2773          | 0.9161    |
| 0.0501        | 15.5  | 1984 | 0.2908          | 0.9161    |
| 0.0518        | 16.0  | 2048 | 0.3022          | 0.9128    |
| 0.0515        | 16.5  | 2112 | 0.3325          | 0.9228    |
| 0.0537        | 17.0  | 2176 | 0.3087          | 0.9195    |
| 0.0462        | 17.5  | 2240 | 0.2908          | 0.9295    |
| 0.0406        | 18.0  | 2304 | 0.3139          | 0.9262    |
| 0.0283        | 18.5  | 2368 | 0.3038          | 0.9329    |
| 0.0196        | 19.0  | 2432 | 0.2968          | 0.9329    |
| 0.0207        | 19.5  | 2496 | 0.3090          | 0.9295    |
| 0.0248        | 20.0  | 2560 | 0.3097          | 0.9262    |
| 0.0223        | 20.5  | 2624 | 0.2872          | 0.9262    |
| 0.0205        | 21.0  | 2688 | 0.3517          | 0.9262    |
| 0.0192        | 21.5  | 2752 | 0.3580          | 0.9295    |
| 0.0238        | 22.0  | 2816 | 0.3922          | 0.9262    |
| 0.0173        | 22.5  | 2880 | 0.3709          | 0.9228    |
| 0.019         | 23.0  | 2944 | 0.3679          | 0.9295    |
| 0.0132        | 23.5  | 3008 | 0.3949          | 0.9295    |
| 0.0112        | 24.0  | 3072 | 0.3609          | 0.9329    |
| 0.0122        | 24.5  | 3136 | 0.3732          | 0.9262    |
| 0.0107        | 25.0  | 3200 | 0.3667          | 0.9295    |
| 0.0116        | 25.5  | 3264 | 0.3775          | 0.9262    |
| 0.0111        | 26.0  | 3328 | 0.3289          | 0.9262    |
| 0.0151        | 26.5  | 3392 | 0.3770          | 0.9228    |
| 0.0139        | 27.0  | 3456 | 0.3755          | 0.9228    |
| 0.0117        | 27.5  | 3520 | 0.4131          | 0.9195    |
| 0.0086        | 28.0  | 3584 | 0.3856          | 0.9262    |
| 0.0101        | 28.5  | 3648 | 0.3674          | 0.9362    |
| 0.0097        | 29.0  | 3712 | 0.3762          | 0.9396    |
| 0.0086        | 29.5  | 3776 | 0.4119          | 0.9295    |
| 0.0091        | 30.0  | 3840 | 0.3882          | 0.9362    |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1