---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
model-index:
- name: ryan_model3272024
  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_model3272024

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: 0.3037
- Na Accuracy: 0.7297
- Ordinal Accuracy: 0.5285
- Ordinal Mae: 0.6723

## 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 | Ordinal Mae |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:|
| 0.4062        | 0.13  | 25   | 0.3799          | 0.6216      | 0.2395           | 0.9244      |
| 0.3536        | 0.27  | 50   | 0.3700          | 0.6757      | 0.3840           | 0.9067      |
| 0.4295        | 0.4   | 75   | 0.3405          | 0.7838      | 0.2966           | 0.8798      |
| 0.4114        | 0.53  | 100  | 0.3906          | 0.7297      | 0.3536           | 0.8806      |
| 0.3521        | 0.66  | 125  | 0.3530          | 0.8108      | 0.4259           | 0.8442      |
| 0.3349        | 0.8   | 150  | 0.3412          | 0.7297      | 0.4753           | 0.8016      |
| 0.4612        | 0.93  | 175  | 0.3639          | 0.5405      | 0.4677           | 0.7604      |
| 0.2424        | 1.06  | 200  | 0.3297          | 0.7027      | 0.4867           | 0.7117      |
| 0.2928        | 1.2   | 225  | 0.3494          | 0.6757      | 0.5285           | 0.6955      |
| 0.2436        | 1.33  | 250  | 0.3037          | 0.7297      | 0.5285           | 0.6723      |
| 0.2776        | 1.46  | 275  | 0.3366          | 0.5946      | 0.5171           | 0.6727      |


### Framework versions

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