---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
model-index:
- name: ryan_model314
  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. -->

# ryan_model314

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 beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2404
- Na Accuracy: 0.96
- Ordinal Accuracy: 0.5921

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Na Accuracy | Ordinal Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|
| 0.3682        | 0.32  | 100  | 0.3209          | 0.942       | 0.5268           |
| 0.2877        | 0.64  | 200  | 0.2783          | 0.944       | 0.5921           |
| 0.3079        | 0.96  | 300  | 0.2544          | 0.958       | 0.5338           |
| 0.1901        | 1.28  | 400  | 0.2632          | 0.948       | 0.6061           |
| 0.277         | 1.6   | 500  | 0.2404          | 0.96        | 0.5921           |
| 0.2081        | 1.92  | 600  | 0.2585          | 0.95        | 0.6270           |
| 0.0809        | 2.24  | 700  | 0.2631          | 0.954       | 0.6737           |
| 0.1           | 2.56  | 800  | 0.2693          | 0.958       | 0.6364           |
| 0.0924        | 2.88  | 900  | 0.2566          | 0.962       | 0.6503           |
| 0.0304        | 3.19  | 1000 | 0.2782          | 0.954       | 0.6527           |
| 0.0256        | 3.51  | 1100 | 0.2662          | 0.96        | 0.6643           |
| 0.0424        | 3.83  | 1200 | 0.2670          | 0.962       | 0.6760           |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2