---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
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: 0.6533333333333333
---

<!-- 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: 0.2071
- Recall: 0.6533

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 9    | 0.6362          | 0.3333 |
| No log        | 2.0   | 18   | 0.4641          | 0.0    |
| No log        | 3.0   | 27   | 0.3251          | 0.0    |
| No log        | 4.0   | 36   | 0.2605          | 0.0    |
| No log        | 5.0   | 45   | 0.2100          | 0.0    |
| No log        | 6.0   | 54   | 0.1943          | 0.08   |
| No log        | 7.0   | 63   | 0.1986          | 0.64   |
| No log        | 8.0   | 72   | 0.1856          | 0.6933 |
| No log        | 9.0   | 81   | 0.1654          | 0.6933 |
| No log        | 10.0  | 90   | 0.1593          | 0.72   |
| No log        | 11.0  | 99   | 0.1638          | 0.68   |
| No log        | 12.0  | 108  | 0.1732          | 0.6933 |
| No log        | 13.0  | 117  | 0.1748          | 0.56   |
| No log        | 14.0  | 126  | 0.1792          | 0.6533 |
| No log        | 15.0  | 135  | 0.1743          | 0.84   |
| No log        | 16.0  | 144  | 0.1760          | 0.5733 |
| No log        | 17.0  | 153  | 0.1641          | 0.6    |
| No log        | 18.0  | 162  | 0.1558          | 0.76   |
| No log        | 19.0  | 171  | 0.2121          | 0.7867 |
| No log        | 20.0  | 180  | 0.1765          | 0.56   |
| No log        | 21.0  | 189  | 0.1802          | 0.7733 |
| No log        | 22.0  | 198  | 0.1729          | 0.7467 |
| No log        | 23.0  | 207  | 0.2004          | 0.48   |
| No log        | 24.0  | 216  | 0.1794          | 0.72   |
| No log        | 25.0  | 225  | 0.2185          | 0.7867 |
| No log        | 26.0  | 234  | 0.2115          | 0.8533 |
| No log        | 27.0  | 243  | 0.1999          | 0.7067 |
| No log        | 28.0  | 252  | 0.1900          | 0.5467 |
| No log        | 29.0  | 261  | 0.2158          | 0.72   |
| No log        | 30.0  | 270  | 0.2515          | 0.8533 |
| No log        | 31.0  | 279  | 0.2322          | 0.7733 |
| No log        | 32.0  | 288  | 0.2024          | 0.8    |
| No log        | 33.0  | 297  | 0.2342          | 0.76   |
| No log        | 34.0  | 306  | 0.2205          | 0.7467 |
| No log        | 35.0  | 315  | 0.1820          | 0.7067 |
| No log        | 36.0  | 324  | 0.2169          | 0.68   |
| No log        | 37.0  | 333  | 0.2170          | 0.6133 |
| No log        | 38.0  | 342  | 0.1767          | 0.68   |
| No log        | 39.0  | 351  | 0.2326          | 0.8133 |
| No log        | 40.0  | 360  | 0.2386          | 0.76   |
| No log        | 41.0  | 369  | 0.2431          | 0.68   |
| No log        | 42.0  | 378  | 0.2160          | 0.6933 |
| No log        | 43.0  | 387  | 0.2234          | 0.76   |
| No log        | 44.0  | 396  | 0.2491          | 0.7467 |
| No log        | 45.0  | 405  | 0.2342          | 0.6933 |
| No log        | 46.0  | 414  | 0.2124          | 0.7333 |
| No log        | 47.0  | 423  | 0.2602          | 0.6533 |
| No log        | 48.0  | 432  | 0.2702          | 0.6133 |
| No log        | 49.0  | 441  | 0.2258          | 0.6533 |
| No log        | 50.0  | 450  | 0.2158          | 0.64   |
| No log        | 51.0  | 459  | 0.2071          | 0.6533 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1