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

<!-- 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. -->

# snacks_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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4458
- Accuracy: 0.8942

## 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: 0.0001
- 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: linear
- num_epochs: 13

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 303  | 0.7200          | 0.8649   |
| 1.0168        | 2.0   | 606  | 0.5468          | 0.8723   |
| 1.0168        | 3.0   | 909  | 0.4612          | 0.8848   |
| 0.3765        | 4.0   | 1212 | 0.5239          | 0.8660   |
| 0.2585        | 5.0   | 1515 | 0.4193          | 0.8890   |
| 0.2585        | 6.0   | 1818 | 0.4571          | 0.8775   |
| 0.2038        | 7.0   | 2121 | 0.4538          | 0.8838   |
| 0.2038        | 8.0   | 2424 | 0.4508          | 0.8880   |
| 0.1827        | 9.0   | 2727 | 0.4748          | 0.8880   |
| 0.1568        | 10.0  | 3030 | 0.4928          | 0.8764   |
| 0.1568        | 11.0  | 3333 | 0.3684          | 0.9099   |
| 0.1305        | 12.0  | 3636 | 0.4205          | 0.8984   |
| 0.1305        | 13.0  | 3939 | 0.4537          | 0.8963   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2