---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- arrow
metrics:
- accuracy
model-index:
- name: vit-base-beans
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: arrow
      type: arrow
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9924812030075187
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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 arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0667
- Accuracy: 0.9925

## 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: 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 | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 0.2797        | 1.0   | 130  | 0.9624   | 0.2229          |
| 0.1283        | 2.0   | 260  | 0.9774   | 0.1240          |
| 0.1325        | 3.0   | 390  | 0.9774   | 0.0953          |
| 0.0809        | 4.0   | 520  | 0.9925   | 0.0667          |
| 0.1164        | 5.0   | 650  | 0.9774   | 0.0842          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1