SwinV2-Base-30VN-Food
This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12-192-22k on the vuongnhathien/30VNFoods dataset. It achieves the following results on the evaluation set:
- Loss: 0.4828
- Accuracy: 0.8629
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: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8268 | 1.0 | 275 | 0.5937 | 0.8270 |
| 0.5113 | 2.0 | 550 | 0.5267 | 0.8545 |
| 0.331 | 3.0 | 825 | 0.5459 | 0.8545 |
| 0.2273 | 4.0 | 1100 | 0.6090 | 0.8441 |
| 0.1384 | 5.0 | 1375 | 0.6096 | 0.8736 |
| 0.0918 | 6.0 | 1650 | 0.6669 | 0.8414 |
| 0.0616 | 7.0 | 1925 | 0.6487 | 0.8891 |
| 0.0307 | 8.0 | 2200 | 0.6908 | 0.8787 |
| 0.0173 | 9.0 | 2475 | 0.6673 | 0.8938 |
| 0.0109 | 10.0 | 2750 | 0.6488 | 0.9014 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Evaluation results
- Accuracy on vuongnhathien/30VNFoodsvalidation set self-reported0.863