---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-type
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7583333333333333
---

<!-- 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-patch16-224-type

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7249
- Accuracy: 0.7583

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4991        | 0.99  | 78   | 1.2167          | 0.6019   |
| 1.0157        | 1.99  | 157  | 0.8529          | 0.7083   |
| 0.8163        | 3.0   | 236  | 0.7725          | 0.7287   |
| 0.7916        | 4.0   | 315  | 0.7622          | 0.7343   |
| 0.6525        | 4.99  | 393  | 0.7374          | 0.7361   |
| 0.6159        | 5.99  | 472  | 0.7188          | 0.75     |
| 0.5413        | 7.0   | 551  | 0.7029          | 0.7463   |
| 0.4838        | 8.0   | 630  | 0.7254          | 0.7352   |
| 0.4587        | 8.99  | 708  | 0.7219          | 0.7565   |
| 0.4332        | 9.99  | 787  | 0.7077          | 0.7528   |
| 0.379         | 11.0  | 866  | 0.7106          | 0.7583   |
| 0.4181        | 12.0  | 945  | 0.7158          | 0.7556   |
| 0.3798        | 12.99 | 1023 | 0.7234          | 0.7537   |
| 0.3841        | 13.99 | 1102 | 0.7211          | 0.7556   |
| 0.3464        | 14.86 | 1170 | 0.7249          | 0.7583   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0