---
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
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.48125
---

<!-- 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: 1.3523
- Accuracy: 0.4813

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.093         | 1.0   | 10   | 1.8451          | 0.3312   |
| 1.4651        | 2.0   | 20   | 1.6375          | 0.3812   |
| 1.033         | 3.0   | 30   | 1.5209          | 0.3875   |
| 0.7164        | 4.0   | 40   | 1.4455          | 0.4375   |
| 0.4719        | 5.0   | 50   | 1.3971          | 0.425    |
| 0.3109        | 6.0   | 60   | 1.3746          | 0.475    |
| 0.2034        | 7.0   | 70   | 1.3600          | 0.45     |
| 0.1403        | 8.0   | 80   | 1.3523          | 0.4813   |
| 0.1074        | 9.0   | 90   | 1.3493          | 0.4813   |
| 0.0931        | 10.0  | 100  | 1.3471          | 0.475    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1