---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: hf_images_model1
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9178265524625268
---

<!-- 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. -->

# hf_images_model1

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 image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2058
- Accuracy: 0.9178

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7057        | 0.04  | 10   | 0.7027          | 0.4644   |
| 0.6808        | 0.09  | 20   | 0.6615          | 0.6590   |
| 0.6278        | 0.13  | 30   | 0.5969          | 0.7441   |
| 0.5674        | 0.17  | 40   | 0.5134          | 0.8183   |
| 0.4761        | 0.21  | 50   | 0.4146          | 0.875    |
| 0.3777        | 0.26  | 60   | 0.3362          | 0.8796   |
| 0.303         | 0.3   | 70   | 0.2906          | 0.8854   |
| 0.2385        | 0.34  | 80   | 0.2694          | 0.8937   |
| 0.2452        | 0.39  | 90   | 0.2515          | 0.9012   |
| 0.2771        | 0.43  | 100  | 0.2441          | 0.9050   |
| 0.2332        | 0.47  | 110  | 0.2510          | 0.8975   |
| 0.2495        | 0.51  | 120  | 0.2398          | 0.9052   |
| 0.2611        | 0.56  | 130  | 0.2384          | 0.9063   |
| 0.2292        | 0.6   | 140  | 0.2931          | 0.8865   |
| 0.2518        | 0.64  | 150  | 0.2537          | 0.8994   |
| 0.211         | 0.69  | 160  | 0.2619          | 0.8953   |
| 0.2514        | 0.73  | 170  | 0.2236          | 0.9090   |
| 0.2272        | 0.77  | 180  | 0.2254          | 0.9085   |
| 0.2263        | 0.81  | 190  | 0.2141          | 0.9181   |
| 0.2524        | 0.86  | 200  | 0.2038          | 0.9194   |
| 0.2024        | 0.9   | 210  | 0.2038          | 0.9165   |
| 0.2355        | 0.94  | 220  | 0.2215          | 0.9103   |
| 0.2431        | 0.99  | 230  | 0.2116          | 0.9178   |
| 0.1921        | 1.03  | 240  | 0.2105          | 0.9111   |
| 0.1845        | 1.07  | 250  | 0.2107          | 0.9117   |
| 0.1838        | 1.11  | 260  | 0.2070          | 0.9119   |
| 0.1824        | 1.16  | 270  | 0.2110          | 0.9130   |
| 0.1706        | 1.2   | 280  | 0.2177          | 0.9154   |
| 0.1826        | 1.24  | 290  | 0.2058          | 0.9160   |
| 0.1816        | 1.28  | 300  | 0.2081          | 0.9176   |
| 0.1901        | 1.33  | 310  | 0.2187          | 0.9149   |
| 0.2112        | 1.37  | 320  | 0.2107          | 0.9181   |
| 0.22          | 1.41  | 330  | 0.2065          | 0.9173   |
| 0.2105        | 1.46  | 340  | 0.2090          | 0.9170   |
| 0.2016        | 1.5   | 350  | 0.2044          | 0.9141   |
| 0.2055        | 1.54  | 360  | 0.2029          | 0.9173   |
| 0.1507        | 1.58  | 370  | 0.2103          | 0.9192   |
| 0.1705        | 1.63  | 380  | 0.1960          | 0.9184   |
| 0.1605        | 1.67  | 390  | 0.2070          | 0.9154   |
| 0.2011        | 1.71  | 400  | 0.2096          | 0.9160   |
| 0.1832        | 1.76  | 410  | 0.2023          | 0.9176   |
| 0.1756        | 1.8   | 420  | 0.2005          | 0.9189   |
| 0.1874        | 1.84  | 430  | 0.2050          | 0.9135   |
| 0.1497        | 1.88  | 440  | 0.1936          | 0.9240   |
| 0.1891        | 1.93  | 450  | 0.1991          | 0.9208   |
| 0.1595        | 1.97  | 460  | 0.2014          | 0.9194   |
| 0.2028        | 2.01  | 470  | 0.1994          | 0.9184   |
| 0.1794        | 2.06  | 480  | 0.2068          | 0.9146   |
| 0.1404        | 2.1   | 490  | 0.2046          | 0.9181   |
| 0.1615        | 2.14  | 500  | 0.1955          | 0.9243   |
| 0.1555        | 2.18  | 510  | 0.2027          | 0.9202   |
| 0.151         | 2.23  | 520  | 0.1893          | 0.9261   |
| 0.1676        | 2.27  | 530  | 0.2046          | 0.9192   |
| 0.1744        | 2.31  | 540  | 0.1967          | 0.9218   |
| 0.1644        | 2.36  | 550  | 0.1970          | 0.9226   |
| 0.2048        | 2.4   | 560  | 0.1930          | 0.9243   |
| 0.1649        | 2.44  | 570  | 0.1986          | 0.9218   |
| 0.1435        | 2.48  | 580  | 0.1956          | 0.9213   |
| 0.1598        | 2.53  | 590  | 0.1986          | 0.9197   |
| 0.1513        | 2.57  | 600  | 0.2020          | 0.9173   |
| 0.1769        | 2.61  | 610  | 0.2005          | 0.9170   |
| 0.1488        | 2.66  | 620  | 0.2033          | 0.9197   |
| 0.1636        | 2.7   | 630  | 0.1964          | 0.9216   |
| 0.1583        | 2.74  | 640  | 0.1985          | 0.9189   |
| 0.1294        | 2.78  | 650  | 0.2109          | 0.9151   |
| 0.1585        | 2.83  | 660  | 0.2000          | 0.9186   |
| 0.1531        | 2.87  | 670  | 0.2078          | 0.9178   |
| 0.1294        | 2.91  | 680  | 0.1891          | 0.9272   |
| 0.1612        | 2.96  | 690  | 0.2058          | 0.9178   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3