vit-base-seed-3e-4
This model is a fine-tuned version of google/vit-base-patch16-224 on the vuongnhathien/30VNFoods dataset. It achieves the following results on the evaluation set:
- Loss: 0.5610
- Accuracy: 0.8833
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: 0.0003
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6318 | 1.0 | 275 | 0.5698 | 0.8334 |
| 0.3202 | 2.0 | 550 | 0.5532 | 0.8517 |
| 0.1637 | 3.0 | 825 | 0.5996 | 0.8509 |
| 0.0973 | 4.0 | 1100 | 0.6282 | 0.8545 |
| 0.0358 | 5.0 | 1375 | 0.6156 | 0.8604 |
| 0.0234 | 6.0 | 1650 | 0.5977 | 0.8696 |
| 0.0059 | 7.0 | 1925 | 0.5482 | 0.8863 |
| 0.0046 | 8.0 | 2200 | 0.5505 | 0.8839 |
| 0.0018 | 9.0 | 2475 | 0.5506 | 0.8843 |
| 0.0028 | 10.0 | 2750 | 0.5509 | 0.8843 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
google/vit-base-patch16-224Evaluation results
- Accuracy on vuongnhathien/30VNFoodsvalidation set self-reported0.883