---
license: apache-2.0
base_model: google/vit-large-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: 0.51875
---

<!-- 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-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5386
- Accuracy: 0.5188

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0473        | 1.0   | 20   | 2.0179          | 0.175    |
| 1.6184        | 2.0   | 40   | 1.7787          | 0.2437   |
| 1.2134        | 3.0   | 60   | 1.5985          | 0.3625   |
| 1.0157        | 4.0   | 80   | 1.3311          | 0.4813   |
| 0.8578        | 5.0   | 100  | 1.3041          | 0.4875   |
| 0.6496        | 6.0   | 120  | 1.3222          | 0.5062   |
| 0.5972        | 7.0   | 140  | 1.5594          | 0.4562   |
| 0.5073        | 8.0   | 160  | 1.4126          | 0.4813   |
| 0.3964        | 9.0   | 180  | 1.3702          | 0.525    |
| 0.4054        | 10.0  | 200  | 1.3894          | 0.5188   |
| 0.2845        | 11.0  | 220  | 1.4471          | 0.5188   |
| 0.2262        | 12.0  | 240  | 1.5165          | 0.525    |
| 0.2412        | 13.0  | 260  | 1.4684          | 0.5125   |
| 0.2229        | 14.0  | 280  | 1.4005          | 0.525    |
| 0.2078        | 15.0  | 300  | 1.5629          | 0.5062   |
| 0.1619        | 16.0  | 320  | 1.6014          | 0.525    |
| 0.1834        | 17.0  | 340  | 1.4821          | 0.5125   |
| 0.1594        | 18.0  | 360  | 1.5195          | 0.5375   |
| 0.1249        | 19.0  | 380  | 1.5585          | 0.5188   |
| 0.1117        | 20.0  | 400  | 1.4735          | 0.5687   |


### Framework versions

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