---
datasets:
- rice
metrics:
- accuracy
model-index:
- name: rice_classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: rice
      type: rice
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9768
---

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# image_classification

This model is a CNN model on the rice dataset to classify rice into 5 classes (Arborio, Basmati, Ipsala, Jasmine and Karacadag).
It achieves the following results on the evaluation set:
- Loss: 0.0116
- Accuracy: 0.9768

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- optimizer: Adam
- num_epochs: 5

### Training results

| Epoch | Loss   | Accuracy |
|:-----:|:------:|:--------:|
| 1.0   | 0.0510 | 0.9363   |
| 2.0   | 0.0099 | 0.9695   |
| 3.0   | 0.5962 | 0.9767   |
| 4.0   | 0.4232 | 0.9828   |
| 5.0   | 0.0011 | 0.9859   |