---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Image-Classification
  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: 0.55625
---

<!-- 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. -->

# Image-Classification

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2851
- Accuracy: 0.5563

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9706        | 1.0   | 20   | 1.9258          | 0.35     |
| 1.672         | 2.0   | 40   | 1.7025          | 0.4625   |
| 1.4489        | 3.0   | 60   | 1.5581          | 0.4313   |
| 1.2031        | 4.0   | 80   | 1.4534          | 0.5      |
| 0.9503        | 5.0   | 100  | 1.3794          | 0.5      |
| 0.758         | 6.0   | 120  | 1.3283          | 0.5312   |
| 0.6021        | 7.0   | 140  | 1.3007          | 0.5125   |
| 0.4784        | 8.0   | 160  | 1.2851          | 0.5563   |
| 0.3682        | 9.0   | 180  | 1.2815          | 0.525    |
| 0.3117        | 10.0  | 200  | 1.3074          | 0.5125   |
| 0.2753        | 11.0  | 220  | 1.2945          | 0.525    |
| 0.2585        | 12.0  | 240  | 1.2903          | 0.5375   |
| 0.2483        | 13.0  | 260  | 1.2903          | 0.5437   |
| 0.245         | 14.0  | 280  | 1.2927          | 0.5375   |
| 0.2459        | 15.0  | 300  | 1.2925          | 0.5375   |


### Framework versions

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