---
base_model: google/vit-base-patch16-224-in21k
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- image-classification
- vision
- generated_from_trainer
model-index:
- name: vit-base-beans
  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

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: 0.0466
- Accuracy: 0.9774

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2167        | 1.0   | 130  | 0.1714          | 0.9474   |
| 0.1288        | 2.0   | 260  | 0.1307          | 0.9549   |
| 0.1056        | 3.0   | 390  | 0.0669          | 0.9774   |
| 0.0772        | 4.0   | 520  | 0.0466          | 0.9774   |
| 0.0941        | 5.0   | 650  | 0.0804          | 0.9699   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1