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---
license: apache-2.0
base_model: microsoft/resnet-18
tags:
- generated_from_trainer
model-index:
- name: resnet18-food-classifier
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Model description
This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co./microsoft/resnet-18) on an [custom](https://www.kaggle.com/datasets/faldoae/padangfood) 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
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