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Model description
This model is a fine-tuned version of microsoft/resnet-18 on an custom dataset. This model was built using the "Padang Cuisine (Indonesian Food Image Classification)" dataset obtained from Kaggle. During the model building process, this was done using the Pytorch framework with pre-trained Resnet-18. The method used during the process of building this classification model is fine-tuning with the dataset.
Training results
| Epoch | Accuracy |
|---|---|
| 1.0 | 0.6030 |
| 2.0 | 0.8342 |
| 3.0 | 0.8442 |
| 4.0 | 0.8191 |
| 5.0 | 0.8693 |
| 6.0 | 0.8643 |
| 7.0 | 0.8744 |
| 8.0 | 0.8643 |
| 9.0 | 0.8744 |
| 10.0 | 0.8744 |
| 11.0 | 0.8794 |
| 12.0 | 0.8744 |
| 13.0 | 0.8894 |
| 14.0 | 0.8794 |
| 15.0 | 0.8945 |
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- loss_function = CrossEntropyLoss
- optimizer = AdamW
- learning_rate: 0.00001
- batch_size: 16
- num_epochs: 15
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
