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--- |
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license: apache-2.0 |
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base_model: microsoft/resnet-18 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: resnet18-food-classifier |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Model description |
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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. |
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## Training results |
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| Epoch | Accuracy | |
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|:-----:|:--------:| |
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| 1.0 | 0.6030 | |
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| 2.0 | 0.8342 | |
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| 3.0 | 0.8442 | |
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| 4.0 | 0.8191 | |
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| 5.0 | 0.8693 | |
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| 6.0 | 0.8643 | |
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| 7.0 | 0.8744 | |
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| 8.0 | 0.8643 | |
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| 9.0 | 0.8744 | |
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| 10.0 | 0.8744 | |
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| 11.0 | 0.8794 | |
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| 12.0 | 0.8744 | |
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| 13.0 | 0.8894 | |
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| 14.0 | 0.8794 | |
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| 15.0 | 0.8945 | |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- loss_function = CrossEntropyLoss |
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- optimizer = AdamW |
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- learning_rate: 0.00001 |
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- batch_size: 16 |
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- num_epochs: 15 |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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