en region:us
---
language:
- en
metrics:
- accuracy
---
# indonesian food_classification

This model is a fine-tuned version of torchvision.models.wide_resnet50_2 on the indonesian-food-dataset.
It achieves the following results on the evaluation set:
- Loss: 0.574
- Accuracy: 0.8171

## Model description

This model is based on the torchvision.models.wide_resnet50_2 architecture, which is a pre-trained model. 
The model has fine-tuned for a specific task using the Indonesian Food Dataset.

## Intended uses & limitations

Intended Uses: This model is intended for image classification tasks, specifically for classifying Indonesian food items in the Indonesian Food Dataset.
Limitations: Deep learning models require a large amount of data for training. They might not perform well if the dataset is small or not representative

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.01
- train_batch_size: 50
- eval_batch_size: 32
- optimizer: SGD
- lr_scheduler_type: MultiStepLr
- num_epochs: 100

### Training results
Best Accuracy Achieved: 0.8171