---
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: 0.7818181818181819
---

<!-- 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: 0.3844
- Recall: 0.7818

## 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   | 11   | 0.4763          | 0.6987 |
| No log        | 2.0   | 22   | 0.4438          | 0.6390 |
| No log        | 3.0   | 33   | 0.4511          | 0.5870 |
| No log        | 4.0   | 44   | 0.4084          | 0.7610 |
| No log        | 5.0   | 55   | 0.3562          | 0.8078 |
| No log        | 6.0   | 66   | 0.3844          | 0.7818 |


### Framework versions

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