---
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: 0.7423708920187794
---

<!-- 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: 0.7556
- Accuracy: 0.7424

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5461        | 1.0   | 62   | 0.7743          | 0.7230   |
| 0.4924        | 1.99  | 124  | 0.7858          | 0.7248   |
| 0.5121        | 2.99  | 186  | 0.7973          | 0.7330   |
| 0.5216        | 4.0   | 249  | 0.7749          | 0.7289   |
| 0.5788        | 5.0   | 311  | 0.7801          | 0.7312   |
| 0.5863        | 5.99  | 373  | 0.7705          | 0.7424   |
| 0.5862        | 6.99  | 435  | 0.7560          | 0.7424   |
| 0.5327        | 8.0   | 498  | 0.7631          | 0.7365   |
| 0.5155        | 9.0   | 560  | 0.7560          | 0.7406   |
| 0.511         | 9.96  | 620  | 0.7556          | 0.7424   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1