vit-base-1e-4-20ep
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: 0.4034
- Accuracy: 0.8873
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: 0.0001
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5376 | 1.0 | 275 | 0.4677 | 0.8640 |
| 0.2085 | 2.0 | 550 | 0.4375 | 0.8811 |
| 0.0755 | 3.0 | 825 | 0.4605 | 0.8899 |
| 0.0429 | 4.0 | 1100 | 0.4784 | 0.8879 |
| 0.0146 | 5.0 | 1375 | 0.5386 | 0.8799 |
| 0.0176 | 6.0 | 1650 | 0.5524 | 0.8803 |
| 0.0137 | 7.0 | 1925 | 0.5249 | 0.8887 |
| 0.0076 | 8.0 | 2200 | 0.5401 | 0.8942 |
| 0.0026 | 9.0 | 2475 | 0.5477 | 0.8934 |
| 0.0054 | 10.0 | 2750 | 0.5417 | 0.8946 |
| 0.0034 | 11.0 | 3025 | 0.5430 | 0.8974 |
| 0.0033 | 12.0 | 3300 | 0.5443 | 0.8954 |
| 0.0027 | 13.0 | 3575 | 0.5423 | 0.8986 |
| 0.0024 | 14.0 | 3850 | 0.5434 | 0.8990 |
| 0.0027 | 15.0 | 4125 | 0.5483 | 0.8962 |
| 0.0027 | 16.0 | 4400 | 0.5485 | 0.8998 |
| 0.0019 | 17.0 | 4675 | 0.5502 | 0.8998 |
| 0.0022 | 18.0 | 4950 | 0.5508 | 0.8998 |
| 0.0015 | 19.0 | 5225 | 0.5509 | 0.9002 |
| 0.002 | 20.0 | 5500 | 0.5510 | 0.9010 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2