---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- fruits
- vegetables
- food
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: less-augmentation-fruits-and-vegetables-vit
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: less-augmentation-fruits-and-vegetables-vit
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9303621169916435
---

<!-- 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. -->

# less-augmentation-fruits-and-vegetables-vit

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the less-augmentation-fruits-and-vegetables-vit dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2129
- Accuracy: 0.9304

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.809         | 1.0   | 195  | 0.2873          | 0.9145   |
| 0.5755        | 2.0   | 390  | 0.2350          | 0.9202   |
| 0.5052        | 3.0   | 585  | 0.2173          | 0.9145   |
| 0.4884        | 4.0   | 780  | 0.2104          | 0.9288   |
| 0.4518        | 5.0   | 975  | 0.2079          | 0.9288   |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1