---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- recall
model-index:
- name: vca
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Recall
      type: recall
      value: 0.7866666666666666
---

<!-- 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. -->

# vca

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: 0.2021
- Recall: 0.7867

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 9    | 0.4676          | 0.0    |
| No log        | 2.0   | 18   | 0.2918          | 0.0    |
| No log        | 3.0   | 27   | 0.2191          | 0.0    |
| No log        | 4.0   | 36   | 0.1971          | 0.1733 |
| No log        | 5.0   | 45   | 0.1695          | 0.4133 |
| No log        | 6.0   | 54   | 0.1693          | 0.52   |
| No log        | 7.0   | 63   | 0.1597          | 0.5867 |
| No log        | 8.0   | 72   | 0.1863          | 0.7733 |
| No log        | 9.0   | 81   | 0.1591          | 0.72   |
| No log        | 10.0  | 90   | 0.1543          | 0.72   |
| No log        | 11.0  | 99   | 0.1559          | 0.6933 |
| No log        | 12.0  | 108  | 0.1658          | 0.7333 |
| No log        | 13.0  | 117  | 0.1691          | 0.6533 |
| No log        | 14.0  | 126  | 0.1779          | 0.68   |
| No log        | 15.0  | 135  | 0.1635          | 0.8133 |
| No log        | 16.0  | 144  | 0.1765          | 0.6933 |
| No log        | 17.0  | 153  | 0.1679          | 0.7333 |
| No log        | 18.0  | 162  | 0.1694          | 0.7467 |
| No log        | 19.0  | 171  | 0.1770          | 0.8133 |
| No log        | 20.0  | 180  | 0.1692          | 0.7867 |
| No log        | 21.0  | 189  | 0.2021          | 0.7867 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3