---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: TransparentBagClassifier
  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: 0.8597560975609756
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# TransparentBagClassifier

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: 0.3956
- Accuracy: 0.8598

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 0.448         | 1.0   | 82   | 0.7304   | 0.5725          |
| 0.5097        | 2.0   | 164  | 0.7652   | 0.4946          |
| 0.452         | 3.0   | 246  | 0.7565   | 0.4841          |
| 0.3885        | 4.0   | 328  | 0.7565   | 0.4812          |
| 0.4743        | 5.0   | 410  | 0.7739   | 0.4626          |
| 0.4749        | 4.0   | 464  | 0.4572   | 0.7988          |
| 0.4319        | 5.0   | 580  | 0.3956   | 0.8598          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cpu
- Datasets 3.0.0
- Tokenizers 0.19.1