---
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: 1.0327
- Na Accuracy: 0.956
- Ordinal Accuracy: 0.568
- Ordinal Mae: 56.3484

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:|
| 1.3578        | 0.32  | 100  | 1.2058          | 0.944       | 0.54             | 90.9846     |
| 1.089         | 0.64  | 200  | 1.0987          | 0.95        | 0.548            | 120.7097    |
| 0.924         | 0.96  | 300  | 1.0838          | 0.946       | 0.568            | 76.7982     |
| 0.694         | 1.28  | 400  | 1.0680          | 0.942       | 0.556            | 105.6312    |
| 0.7739        | 1.6   | 500  | 1.0327          | 0.956       | 0.568            | 56.3484     |
| 0.5935        | 1.92  | 600  | 1.0479          | 0.932       | 0.598            | 50.4520     |
| 0.3525        | 2.24  | 700  | 1.1915          | 0.94        | 0.578            | 68.5099     |
| 0.2385        | 2.56  | 800  | 1.1303          | 0.948       | 0.586            | 43.0221     |
| 0.3423        | 2.88  | 900  | 1.1767          | 0.94        | 0.604            | 72.1437     |
| 0.0674        | 3.19  | 1000 | 1.2294          | 0.938       | 0.606            | 28.0702     |
| 0.1206        | 3.51  | 1100 | 1.2336          | 0.938       | 0.616            | 65.0794     |
| 0.1261        | 3.83  | 1200 | 1.2907          | 0.938       | 0.604            | 45.8334     |


### Framework versions

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