---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-brand
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8495867768595041
---

<!-- 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. -->

# vit-base-patch16-224-brand

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4812
- Accuracy: 0.8496

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4669        | 1.0   | 88   | 1.3067          | 0.5612   |
| 0.8898        | 1.99  | 176  | 0.8380          | 0.7140   |
| 0.7243        | 2.99  | 264  | 0.6559          | 0.7694   |
| 0.5158        | 4.0   | 353  | 0.5982          | 0.7950   |
| 0.4605        | 5.0   | 441  | 0.5856          | 0.8083   |
| 0.332         | 5.99  | 529  | 0.5138          | 0.8355   |
| 0.3375        | 6.99  | 617  | 0.5095          | 0.8264   |
| 0.2188        | 8.0   | 706  | 0.5089          | 0.8322   |
| 0.2112        | 9.0   | 794  | 0.5126          | 0.8380   |
| 0.1895        | 9.99  | 882  | 0.5057          | 0.8364   |
| 0.1593        | 10.99 | 970  | 0.4852          | 0.8529   |
| 0.1463        | 12.0  | 1059 | 0.4934          | 0.8430   |
| 0.1565        | 13.0  | 1147 | 0.4794          | 0.8496   |
| 0.1236        | 13.99 | 1235 | 0.4863          | 0.8463   |
| 0.1407        | 14.96 | 1320 | 0.4812          | 0.8496   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0