---
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: 0.55
---

<!-- 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: 1.3640
- Accuracy: 0.55

## 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: 2
- 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1309        | 1.0   | 20   | 1.3481          | 0.4938   |
| 1.0746        | 2.0   | 40   | 1.3706          | 0.475    |
| 1.0367        | 3.0   | 60   | 1.3161          | 0.5375   |
| 0.9814        | 4.0   | 80   | 1.3837          | 0.45     |
| 0.886         | 5.0   | 100  | 1.3633          | 0.4875   |
| 0.8096        | 6.0   | 120  | 1.3045          | 0.5125   |
| 0.7669        | 7.0   | 140  | 1.3903          | 0.4938   |
| 0.708         | 8.0   | 160  | 1.2867          | 0.5125   |
| 0.6265        | 9.0   | 180  | 1.2244          | 0.5625   |
| 0.6191        | 10.0  | 200  | 1.3461          | 0.525    |
| 0.5598        | 11.0  | 220  | 1.3266          | 0.5625   |
| 0.4667        | 12.0  | 240  | 1.3050          | 0.5563   |
| 0.4613        | 13.0  | 260  | 1.3329          | 0.5375   |
| 0.4268        | 14.0  | 280  | 1.4020          | 0.5312   |
| 0.4256        | 15.0  | 300  | 1.3770          | 0.5188   |
| 0.3727        | 16.0  | 320  | 1.3655          | 0.5188   |
| 0.316         | 17.0  | 340  | 1.3642          | 0.5188   |
| 0.3223        | 18.0  | 360  | 1.2535          | 0.5938   |
| 0.3064        | 19.0  | 380  | 1.4173          | 0.4875   |
| 0.2866        | 20.0  | 400  | 1.3343          | 0.5625   |
| 0.2781        | 21.0  | 420  | 1.5072          | 0.4813   |
| 0.3027        | 22.0  | 440  | 1.5067          | 0.5125   |
| 0.26          | 23.0  | 460  | 1.4456          | 0.5687   |
| 0.2156        | 24.0  | 480  | 1.4825          | 0.525    |
| 0.1908        | 25.0  | 500  | 1.5369          | 0.5375   |
| 0.213         | 26.0  | 520  | 1.5397          | 0.5188   |
| 0.241         | 27.0  | 540  | 1.4804          | 0.5125   |
| 0.1974        | 28.0  | 560  | 1.5786          | 0.5062   |
| 0.225         | 29.0  | 580  | 1.4677          | 0.5375   |
| 0.2459        | 30.0  | 600  | 1.5392          | 0.5312   |
| 0.2146        | 31.0  | 620  | 1.6734          | 0.4625   |
| 0.1891        | 32.0  | 640  | 1.5012          | 0.55     |
| 0.2231        | 33.0  | 660  | 1.6265          | 0.5      |
| 0.1903        | 34.0  | 680  | 1.5405          | 0.5312   |
| 0.1852        | 35.0  | 700  | 1.6295          | 0.5      |
| 0.1768        | 36.0  | 720  | 1.5758          | 0.5375   |
| 0.1486        | 37.0  | 740  | 1.6176          | 0.5188   |
| 0.1814        | 38.0  | 760  | 1.5107          | 0.5375   |
| 0.1642        | 39.0  | 780  | 1.5315          | 0.55     |
| 0.1822        | 40.0  | 800  | 1.6309          | 0.525    |
| 0.1819        | 41.0  | 820  | 1.7033          | 0.4938   |
| 0.1326        | 42.0  | 840  | 1.6107          | 0.5437   |
| 0.1452        | 43.0  | 860  | 1.6219          | 0.55     |
| 0.128         | 44.0  | 880  | 1.4348          | 0.5813   |
| 0.1103        | 45.0  | 900  | 1.6185          | 0.5687   |
| 0.1386        | 46.0  | 920  | 1.5848          | 0.5312   |
| 0.1021        | 47.0  | 940  | 1.6036          | 0.5563   |
| 0.1414        | 48.0  | 960  | 1.5455          | 0.575    |
| 0.1989        | 49.0  | 980  | 1.5955          | 0.525    |
| 0.1458        | 50.0  | 1000 | 1.5511          | 0.55     |


### Framework versions

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