---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fruits_and_vegetables_image_classification
  results: []
---

<!-- 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. -->

# fruits_and_vegetables_image_classification

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3835
- Accuracy: 0.9159

## 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: 8e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 87   | 1.6751          | 0.8768   |
| No log        | 2.0   | 174  | 1.0260          | 0.8957   |
| No log        | 3.0   | 261  | 0.6767          | 0.8957   |
| No log        | 4.0   | 348  | 0.5445          | 0.8986   |
| No log        | 5.0   | 435  | 0.4685          | 0.9072   |
| 0.8955        | 6.0   | 522  | 0.4328          | 0.9072   |
| 0.8955        | 7.0   | 609  | 0.4028          | 0.9      |
| 0.8955        | 8.0   | 696  | 0.3958          | 0.9145   |
| 0.8955        | 9.0   | 783  | 0.3835          | 0.9159   |
| 0.8955        | 10.0  | 870  | 0.3842          | 0.9145   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0