---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch32-224-in21k
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-patch32-224-in21k](https://huggingface.co/google/vit-base-patch32-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5006
- 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: 2e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0441        | 1.0   | 40   | 2.0365          | 0.25     |
| 1.9219        | 2.0   | 80   | 1.9451          | 0.3063   |
| 1.7429        | 3.0   | 120  | 1.8213          | 0.375    |
| 1.5854        | 4.0   | 160  | 1.7126          | 0.4188   |
| 1.4913        | 5.0   | 200  | 1.6547          | 0.4688   |
| 1.3673        | 6.0   | 240  | 1.6200          | 0.4813   |
| 1.2713        | 7.0   | 280  | 1.5822          | 0.475    |
| 1.1907        | 8.0   | 320  | 1.5639          | 0.4875   |
| 1.0516        | 9.0   | 360  | 1.5441          | 0.4875   |
| 1.0037        | 10.0  | 400  | 1.5285          | 0.4813   |
| 0.9538        | 11.0  | 440  | 1.5229          | 0.4813   |
| 0.8983        | 12.0  | 480  | 1.5100          | 0.4813   |
| 0.8616        | 13.0  | 520  | 1.5016          | 0.4938   |
| 0.8417        | 14.0  | 560  | 1.5024          | 0.4813   |
| 0.8078        | 15.0  | 600  | 1.5006          | 0.4813   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1
- Datasets 2.21.0
- Tokenizers 0.19.1