---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0830
- Accuracy: 0.9699

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2809        | 1.0   | 130  | 0.2194          | 0.9624   |
| 0.1253        | 2.0   | 260  | 0.1309          | 0.9699   |
| 0.1443        | 3.0   | 390  | 0.0952          | 0.9774   |
| 0.0859        | 4.0   | 520  | 0.0628          | 0.9925   |
| 0.1205        | 5.0   | 650  | 0.0830          | 0.9699   |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.0