finetuned-vietnamese-food
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the indian_vietnam_images dataset. It achieves the following results on the evaluation set:
- Loss: 0.3760
- Accuracy: 0.8958
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.1058 | 0.0910 | 100 | 1.9974 | 0.5694 |
1.4012 | 0.1820 | 200 | 1.4076 | 0.6855 |
1.3551 | 0.2730 | 300 | 1.1650 | 0.7264 |
1.1111 | 0.3640 | 400 | 1.0998 | 0.7062 |
1.0038 | 0.4550 | 500 | 0.9087 | 0.7483 |
0.9599 | 0.5460 | 600 | 0.8278 | 0.7682 |
1.0932 | 0.6369 | 700 | 0.9115 | 0.7360 |
0.7807 | 0.7279 | 800 | 0.8011 | 0.7730 |
0.8237 | 0.8189 | 900 | 0.8345 | 0.7726 |
0.7288 | 0.9099 | 1000 | 0.6427 | 0.8258 |
0.7982 | 1.0009 | 1100 | 0.6427 | 0.8215 |
0.7331 | 1.0919 | 1200 | 0.6423 | 0.8183 |
0.6849 | 1.1829 | 1300 | 0.6820 | 0.8151 |
0.671 | 1.2739 | 1400 | 0.6325 | 0.8191 |
0.7307 | 1.3649 | 1500 | 0.6079 | 0.8286 |
0.7499 | 1.4559 | 1600 | 0.5832 | 0.8346 |
0.7004 | 1.5469 | 1700 | 0.6048 | 0.8342 |
0.7543 | 1.6379 | 1800 | 0.5612 | 0.8394 |
0.5557 | 1.7288 | 1900 | 0.5740 | 0.8318 |
0.5019 | 1.8198 | 2000 | 0.5064 | 0.8561 |
0.7043 | 1.9108 | 2100 | 0.5513 | 0.8441 |
0.519 | 2.0018 | 2200 | 0.5862 | 0.8350 |
0.3366 | 2.0928 | 2300 | 0.5159 | 0.8517 |
0.4167 | 2.1838 | 2400 | 0.5386 | 0.8469 |
0.402 | 2.2748 | 2500 | 0.5614 | 0.8374 |
0.4133 | 2.3658 | 2600 | 0.4756 | 0.8652 |
0.4751 | 2.4568 | 2700 | 0.4882 | 0.8612 |
0.3108 | 2.5478 | 2800 | 0.4946 | 0.8648 |
0.3218 | 2.6388 | 2900 | 0.4707 | 0.8680 |
0.282 | 2.7298 | 3000 | 0.4407 | 0.8712 |
0.2823 | 2.8207 | 3100 | 0.4843 | 0.8712 |
0.3498 | 2.9117 | 3200 | 0.4609 | 0.8744 |
0.3196 | 3.0027 | 3300 | 0.4369 | 0.8763 |
0.2822 | 3.0937 | 3400 | 0.4662 | 0.8748 |
0.4166 | 3.1847 | 3500 | 0.4539 | 0.8779 |
0.1904 | 3.2757 | 3600 | 0.4205 | 0.8887 |
0.388 | 3.3667 | 3700 | 0.4163 | 0.8863 |
0.2851 | 3.4577 | 3800 | 0.4168 | 0.8891 |
0.2455 | 3.5487 | 3900 | 0.4004 | 0.8930 |
0.2804 | 3.6397 | 4000 | 0.4044 | 0.8938 |
0.2008 | 3.7307 | 4100 | 0.3833 | 0.8950 |
0.2487 | 3.8217 | 4200 | 0.3812 | 0.8958 |
0.2077 | 3.9126 | 4300 | 0.3760 | 0.8958 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google/vit-base-patch16-224-in21k