---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model-index:
- name: beans_image_classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: beans
      type: beans
      config: default
      split: train[:500]
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.96
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# beans_image_classification

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: 0.1072
- Accuracy: 0.96

## 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: 0.001
- train_batch_size: 12
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.94  | 8    | 1.3666          | 0.66     |
| 0.3651        | 2.0   | 17   | 0.3823          | 0.84     |
| 0.5622        | 2.94  | 25   | 0.3333          | 0.86     |
| 0.3373        | 4.0   | 34   | 0.1274          | 0.97     |
| 0.2055        | 4.94  | 42   | 0.1882          | 0.93     |
| 0.1819        | 6.0   | 51   | 0.2265          | 0.9      |
| 0.1819        | 6.94  | 59   | 0.2395          | 0.91     |
| 0.2428        | 8.0   | 68   | 0.1451          | 0.97     |
| 0.1305        | 8.94  | 76   | 0.1554          | 0.94     |
| 0.1203        | 9.41  | 80   | 0.1705          | 0.92     |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1