---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-game-icons
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: game-icons
      split: train
      args: game-icons
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6548387096774193
---

<!-- 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. -->

# vit-base-game-icons

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: 1.1693
- Accuracy: 0.6548

## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3532        | 1.0   | 440  | 1.4272          | 0.6      |
| 1.2843        | 2.0   | 880  | 1.2953          | 0.6032   |
| 1.1254        | 3.0   | 1320 | 1.2201          | 0.6339   |
| 1.5579        | 4.0   | 1760 | 1.1343          | 0.6677   |
| 1.2813        | 5.0   | 2200 | 1.1693          | 0.6548   |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.12.1