---
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: 0.45
---

<!-- 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: 1.6195
- Accuracy: 0.45

## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 10   | 2.0386          | 0.25     |
| No log        | 2.0   | 20   | 1.9873          | 0.3563   |
| No log        | 3.0   | 30   | 1.9264          | 0.3875   |
| No log        | 4.0   | 40   | 1.8662          | 0.4188   |
| No log        | 5.0   | 50   | 1.8088          | 0.4188   |
| No log        | 6.0   | 60   | 1.7597          | 0.4313   |
| No log        | 7.0   | 70   | 1.7167          | 0.4188   |
| No log        | 8.0   | 80   | 1.6899          | 0.4188   |
| No log        | 9.0   | 90   | 1.6582          | 0.4437   |
| No log        | 10.0  | 100  | 1.6435          | 0.4437   |
| No log        | 11.0  | 110  | 1.6284          | 0.4313   |
| No log        | 12.0  | 120  | 1.6195          | 0.45     |
| No log        | 13.0  | 130  | 1.6141          | 0.45     |
| No log        | 14.0  | 140  | 1.6119          | 0.4437   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1