---
license: apache-2.0
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model-index:
- name: vit-base-beans
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: beans
      type: beans
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8195488721804511
---

<!-- 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-huge-patch14-224-in21k](https://huggingface.co/google/vit-huge-patch14-224-in21k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9760
- Accuracy: 0.8195

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0596        | 1.0   | 259  | 1.0507          | 0.7143   |
| 1.0165        | 2.0   | 518  | 1.0165          | 0.7895   |
| 1.0113        | 3.0   | 777  | 0.9941          | 0.8045   |
| 1.0067        | 4.0   | 1036 | 0.9804          | 0.8195   |
| 0.9746        | 5.0   | 1295 | 0.9760          | 0.8195   |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 1.13.1+cu117-with-pypi-cudnn
- Datasets 2.12.0
- Tokenizers 0.13.3