---
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: 0.5375
---

<!-- 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: 1.3659
- Accuracy: 0.5375

## 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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 32   | 1.9290          | 0.3063   |
| No log        | 2.0   | 64   | 1.6622          | 0.3563   |
| No log        | 3.0   | 96   | 1.5753          | 0.3937   |
| No log        | 4.0   | 128  | 1.5099          | 0.475    |
| No log        | 5.0   | 160  | 1.4614          | 0.4313   |
| No log        | 6.0   | 192  | 1.4104          | 0.5      |
| No log        | 7.0   | 224  | 1.3962          | 0.4562   |
| No log        | 8.0   | 256  | 1.3535          | 0.5437   |
| No log        | 9.0   | 288  | 1.3483          | 0.5062   |
| No log        | 10.0  | 320  | 1.3994          | 0.45     |


### Framework versions

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