---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-beans-demo-v5
  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. -->

# vit-base-beans-demo-v5

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co./google/vit-base-patch16-224-in21k).
It achieves the following results on the evaluation set:
- Loss: 0.0816
- Accuracy: 0.9819

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5092        | 0.28  | 100  | 0.6420          | 0.7681   |
| 0.5076        | 0.56  | 200  | 0.4069          | 0.8722   |
| 0.3291        | 0.83  | 300  | 0.4342          | 0.8569   |
| 0.108         | 1.11  | 400  | 0.2410          | 0.9292   |
| 0.0378        | 1.39  | 500  | 0.3107          | 0.9139   |
| 0.1488        | 1.67  | 600  | 0.1984          | 0.9389   |
| 0.0532        | 1.94  | 700  | 0.1714          | 0.9514   |
| 0.0122        | 2.22  | 800  | 0.1334          | 0.9611   |
| 0.0529        | 2.5   | 900  | 0.1139          | 0.9653   |
| 0.0221        | 2.78  | 1000 | 0.0875          | 0.9736   |
| 0.0052        | 3.06  | 1100 | 0.0816          | 0.9819   |
| 0.0045        | 3.33  | 1200 | 0.0873          | 0.9792   |
| 0.0113        | 3.61  | 1300 | 0.0882          | 0.9833   |
| 0.0043        | 3.89  | 1400 | 0.0865          | 0.9806   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0