---
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: 0.53125
---

<!-- 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: 1.3935
- Accuracy: 0.5312

## 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: 1e-07
- train_batch_size: 27
- eval_batch_size: 27
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 27

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 24   | 1.3599          | 0.5188   |
| No log        | 2.0   | 48   | 1.4076          | 0.475    |
| No log        | 3.0   | 72   | 1.3638          | 0.5375   |
| No log        | 4.0   | 96   | 1.4062          | 0.5375   |
| No log        | 5.0   | 120  | 1.3665          | 0.5563   |
| No log        | 6.0   | 144  | 1.3475          | 0.575    |
| No log        | 7.0   | 168  | 1.3814          | 0.525    |
| No log        | 8.0   | 192  | 1.3791          | 0.5437   |
| No log        | 9.0   | 216  | 1.3692          | 0.5125   |
| No log        | 10.0  | 240  | 1.4024          | 0.5188   |
| No log        | 11.0  | 264  | 1.3544          | 0.5687   |
| No log        | 12.0  | 288  | 1.4049          | 0.5375   |
| No log        | 13.0  | 312  | 1.3539          | 0.5687   |
| No log        | 14.0  | 336  | 1.3936          | 0.5062   |
| No log        | 15.0  | 360  | 1.3643          | 0.5375   |
| No log        | 16.0  | 384  | 1.3618          | 0.5563   |
| No log        | 17.0  | 408  | 1.3669          | 0.5687   |
| No log        | 18.0  | 432  | 1.4041          | 0.5188   |
| No log        | 19.0  | 456  | 1.3679          | 0.5312   |
| No log        | 20.0  | 480  | 1.3489          | 0.5563   |
| 1.1227        | 21.0  | 504  | 1.3575          | 0.575    |
| 1.1227        | 22.0  | 528  | 1.3721          | 0.55     |
| 1.1227        | 23.0  | 552  | 1.3985          | 0.4938   |
| 1.1227        | 24.0  | 576  | 1.3924          | 0.5062   |
| 1.1227        | 25.0  | 600  | 1.3760          | 0.55     |
| 1.1227        | 26.0  | 624  | 1.3767          | 0.5125   |
| 1.1227        | 27.0  | 648  | 1.3627          | 0.5563   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3