---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: results
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train[80%:]
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.0625
---

<!-- 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. -->

# results

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: 4.5590
- Accuracy: 0.0625

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6612        | 1.0   | 40   | 3.9513          | 0.0      |
| 0.8129        | 2.0   | 80   | 3.9721          | 0.025    |
| 0.3799        | 3.0   | 120  | 4.3376          | 0.0125   |
| 0.0946        | 4.0   | 160  | 4.4142          | 0.0563   |
| 0.019         | 5.0   | 200  | 4.5590          | 0.0625   |
| 0.0062        | 6.0   | 240  | 4.9286          | 0.0437   |
| 0.0039        | 7.0   | 280  | 5.0577          | 0.0437   |
| 0.0028        | 8.0   | 320  | 5.1624          | 0.0437   |
| 0.0024        | 9.0   | 360  | 5.2316          | 0.0437   |
| 0.0023        | 10.0  | 400  | 5.2923          | 0.0437   |
| 0.0019        | 11.0  | 440  | 5.3317          | 0.0375   |
| 0.0017        | 12.0  | 480  | 5.3658          | 0.0375   |
| 0.0016        | 13.0  | 520  | 5.3915          | 0.0375   |
| 0.0016        | 14.0  | 560  | 5.4004          | 0.0375   |
| 0.0016        | 15.0  | 600  | 5.4022          | 0.0375   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1