---
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: 0.3295
- 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        | 0.95  | 5    | 0.6389          | 0.0133 |
| No log        | 1.9   | 10   | 0.5645          | 0.0    |
| No log        | 2.86  | 15   | 0.4792          | 0.0    |
| No log        | 4.0   | 21   | 0.4224          | 0.0    |
| No log        | 4.95  | 26   | 0.3652          | 0.0    |
| No log        | 5.9   | 31   | 0.3357          | 0.0    |
| No log        | 6.86  | 36   | 0.2953          | 0.0    |
| No log        | 8.0   | 42   | 0.2909          | 0.0133 |
| No log        | 8.95  | 47   | 0.2937          | 0.7333 |
| No log        | 9.9   | 52   | 0.2718          | 0.68   |
| No log        | 10.86 | 57   | 0.2673          | 0.64   |
| No log        | 12.0  | 63   | 0.3019          | 0.8667 |
| No log        | 12.95 | 68   | 0.2945          | 0.4667 |
| No log        | 13.9  | 73   | 0.2669          | 0.6667 |
| No log        | 14.86 | 78   | 0.2504          | 0.7467 |
| No log        | 16.0  | 84   | 0.2380          | 0.64   |
| No log        | 16.95 | 89   | 0.2525          | 0.64   |
| No log        | 17.9  | 94   | 0.2648          | 0.7467 |
| No log        | 18.86 | 99   | 0.2711          | 0.7067 |
| No log        | 20.0  | 105  | 0.2747          | 0.64   |
| No log        | 20.95 | 110  | 0.2772          | 0.64   |
| No log        | 21.9  | 115  | 0.3000          | 0.6267 |
| No log        | 22.86 | 120  | 0.2871          | 0.5733 |
| No log        | 24.0  | 126  | 0.3025          | 0.6667 |
| No log        | 24.95 | 131  | 0.3317          | 0.5867 |
| No log        | 25.9  | 136  | 0.3171          | 0.5467 |
| No log        | 26.86 | 141  | 0.3322          | 0.64   |
| No log        | 28.0  | 147  | 0.3207          | 0.6533 |
| No log        | 28.95 | 152  | 0.3492          | 0.5733 |
| No log        | 29.9  | 157  | 0.2965          | 0.68   |
| No log        | 30.86 | 162  | 0.3256          | 0.72   |
| No log        | 32.0  | 168  | 0.3460          | 0.6267 |
| No log        | 32.95 | 173  | 0.3118          | 0.7067 |
| No log        | 33.9  | 178  | 0.3656          | 0.6933 |
| No log        | 34.86 | 183  | 0.3111          | 0.5867 |
| No log        | 36.0  | 189  | 0.3119          | 0.6667 |
| No log        | 36.95 | 194  | 0.3524          | 0.72   |
| No log        | 37.9  | 199  | 0.3457          | 0.5333 |
| No log        | 38.86 | 204  | 0.3460          | 0.56   |
| No log        | 40.0  | 210  | 0.3518          | 0.6933 |
| No log        | 40.95 | 215  | 0.2948          | 0.5867 |
| No log        | 41.9  | 220  | 0.3640          | 0.5867 |
| No log        | 42.86 | 225  | 0.3408          | 0.6133 |
| No log        | 44.0  | 231  | 0.3350          | 0.6    |
| No log        | 44.95 | 236  | 0.3832          | 0.72   |
| No log        | 45.9  | 241  | 0.3298          | 0.6667 |
| No log        | 46.86 | 246  | 0.3557          | 0.64   |
| No log        | 48.0  | 252  | 0.3832          | 0.64   |
| No log        | 48.95 | 257  | 0.3317          | 0.6533 |
| No log        | 49.9  | 262  | 0.3980          | 0.6933 |
| No log        | 50.86 | 267  | 0.3295          | 0.6533 |


### Framework versions

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