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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
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