metadata
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_fft
results: []
mobilevit-small_rice-leaf-disease-augmented-v4_fft
This model is a fine-tuned version of apple/mobilevit-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4089
- 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: 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 | Accuracy | Validation Loss |
|---|---|---|---|---|
| 2.0561 | 0.5 | 64 | 0.2886 | 2.0213 |
| 1.9819 | 1.0 | 128 | 0.5503 | 1.8788 |
| 1.771 | 1.5 | 192 | 0.6107 | 1.5291 |
| 1.3911 | 2.0 | 256 | 0.7349 | 1.0706 |
| 1.0026 | 2.5 | 320 | 0.8054 | 0.7560 |
| 0.7657 | 3.0 | 384 | 0.8356 | 0.6180 |
| 0.6082 | 3.5 | 448 | 0.8389 | 0.5422 |
| 0.5313 | 4.0 | 512 | 0.8523 | 0.4946 |
| 0.4623 | 4.5 | 576 | 0.8758 | 0.4512 |
| 0.4212 | 5.0 | 640 | 0.8792 | 0.4322 |
| 0.4025 | 5.5 | 704 | 0.8893 | 0.4259 |
| 0.3892 | 6.0 | 768 | 0.8859 | 0.4238 |
| 0.3959 | 6.5 | 832 | 0.8859 | 0.4083 |
| 0.3279 | 7.0 | 896 | 0.8826 | 0.3750 |
| 0.2793 | 7.5 | 960 | 0.8993 | 0.3350 |
| 0.222 | 8.0 | 1024 | 0.8960 | 0.3208 |
| 0.1862 | 8.5 | 1088 | 0.8993 | 0.3128 |
| 0.1717 | 9.0 | 1152 | 0.9027 | 0.3049 |
| 0.1408 | 9.5 | 1216 | 0.9027 | 0.3010 |
| 0.1507 | 10.0 | 1280 | 0.9161 | 0.3240 |
| 0.1369 | 10.5 | 1344 | 0.9060 | 0.3063 |
| 0.1389 | 11.0 | 1408 | 0.9060 | 0.3045 |
| 0.1199 | 11.5 | 1472 | 0.9094 | 0.3062 |
| 0.1003 | 12.0 | 1536 | 0.9128 | 0.3131 |
| 0.0756 | 12.5 | 1600 | 0.9228 | 0.3002 |
| 0.0636 | 13.0 | 1664 | 0.9128 | 0.3177 |
| 0.058 | 13.5 | 1728 | 0.9228 | 0.3143 |
| 0.0566 | 14.0 | 1792 | 0.9195 | 0.3136 |
| 0.0516 | 14.5 | 1856 | 0.9161 | 0.3447 |
| 0.0426 | 15.0 | 1920 | 0.9228 | 0.2911 |
| 0.0513 | 15.5 | 1984 | 0.3028 | 0.9228 |
| 0.0447 | 16.0 | 2048 | 0.3328 | 0.9195 |
| 0.0332 | 16.5 | 2112 | 0.3193 | 0.9262 |
| 0.0358 | 17.0 | 2176 | 0.3385 | 0.9161 |
| 0.0343 | 17.5 | 2240 | 0.3297 | 0.9295 |
| 0.0291 | 18.0 | 2304 | 0.3518 | 0.9161 |
| 0.0287 | 18.5 | 2368 | 0.3224 | 0.9195 |
| 0.0197 | 19.0 | 2432 | 0.3099 | 0.9228 |
| 0.0223 | 19.5 | 2496 | 0.3305 | 0.9295 |
| 0.0282 | 20.0 | 2560 | 0.3378 | 0.9161 |
| 0.0231 | 20.5 | 2624 | 0.3077 | 0.9228 |
| 0.0251 | 21.0 | 2688 | 0.3520 | 0.9161 |
| 0.021 | 21.5 | 2752 | 0.3506 | 0.9228 |
| 0.0222 | 22.0 | 2816 | 0.3561 | 0.9128 |
| 0.016 | 22.5 | 2880 | 0.3482 | 0.9195 |
| 0.0163 | 23.0 | 2944 | 0.3429 | 0.9228 |
| 0.0114 | 23.5 | 3008 | 0.3839 | 0.9329 |
| 0.0106 | 24.0 | 3072 | 0.4066 | 0.9262 |
| 0.0111 | 24.5 | 3136 | 0.4003 | 0.9329 |
| 0.009 | 25.0 | 3200 | 0.4000 | 0.9262 |
| 0.0088 | 25.5 | 3264 | 0.3667 | 0.9228 |
| 0.0057 | 26.0 | 3328 | 0.3587 | 0.9195 |
| 0.0073 | 26.5 | 3392 | 0.3686 | 0.9329 |
| 0.0085 | 27.0 | 3456 | 0.3676 | 0.9195 |
| 0.0087 | 27.5 | 3520 | 0.4251 | 0.9262 |
| 0.0061 | 28.0 | 3584 | 0.3879 | 0.9195 |
| 0.0062 | 28.5 | 3648 | 0.3865 | 0.9195 |
| 0.0068 | 29.0 | 3712 | 0.3943 | 0.9262 |
| 0.0092 | 29.5 | 3776 | 0.4064 | 0.9228 |
| 0.0078 | 30.0 | 3840 | 0.4089 | 0.9295 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1