---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: minang_food_classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4388888888888889
---

<!-- 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. -->

# minang_food_classification

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8248
- Accuracy: 0.4389

## 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: 1e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2338        | 1.0   | 45   | 2.1647          | 0.1944   |
| 2.1439        | 2.0   | 90   | 2.0883          | 0.2389   |
| 2.0449        | 3.0   | 135  | 2.0265          | 0.2667   |
| 1.9851        | 4.0   | 180  | 1.9385          | 0.3444   |
| 1.9242        | 5.0   | 225  | 1.8869          | 0.3944   |
| 1.8745        | 6.0   | 270  | 1.8432          | 0.4444   |
| 1.831         | 7.0   | 315  | 1.8211          | 0.4556   |
| 1.8017        | 8.0   | 360  | 1.8302          | 0.45     |
| 1.8078        | 9.0   | 405  | 1.8164          | 0.45     |
| 1.7895        | 10.0  | 450  | 1.7973          | 0.4556   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2