---
license: apache-2.0
base_model: microsoft/cvt-13-384-22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cvt-13-384-22k-finetuned-LeafBack
  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: 0.948051948051948
---

<!-- 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. -->

# cvt-13-384-22k-finetuned-LeafBack

This model is a fine-tuned version of [microsoft/cvt-13-384-22k](https://huggingface.co/microsoft/cvt-13-384-22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1695
- Accuracy: 0.9481

## 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: 2e-05
- train_batch_size: 100
- eval_batch_size: 50
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 7    | 0.6404          | 0.6623   |
| No log        | 2.0   | 14   | 0.5304          | 0.7273   |
| No log        | 3.0   | 21   | 0.4551          | 0.7922   |
| No log        | 4.0   | 28   | 0.3175          | 0.8571   |
| No log        | 5.0   | 35   | 0.2922          | 0.8701   |
| No log        | 6.0   | 42   | 0.2964          | 0.8701   |
| No log        | 7.0   | 49   | 0.2839          | 0.8701   |
| No log        | 8.0   | 56   | 0.2930          | 0.8571   |
| No log        | 9.0   | 63   | 0.2856          | 0.8831   |
| No log        | 10.0  | 70   | 0.2969          | 0.8831   |
| No log        | 11.0  | 77   | 0.3002          | 0.8701   |
| No log        | 12.0  | 84   | 0.2919          | 0.8831   |
| No log        | 13.0  | 91   | 0.2780          | 0.8961   |
| No log        | 14.0  | 98   | 0.2733          | 0.8831   |
| No log        | 15.0  | 105  | 0.2489          | 0.8961   |
| No log        | 16.0  | 112  | 0.2569          | 0.8961   |
| No log        | 17.0  | 119  | 0.2371          | 0.9091   |
| No log        | 18.0  | 126  | 0.2367          | 0.9091   |
| No log        | 19.0  | 133  | 0.2297          | 0.9091   |
| No log        | 20.0  | 140  | 0.2170          | 0.9221   |
| No log        | 21.0  | 147  | 0.2132          | 0.9351   |
| No log        | 22.0  | 154  | 0.2080          | 0.9351   |
| No log        | 23.0  | 161  | 0.2010          | 0.9481   |
| No log        | 24.0  | 168  | 0.2106          | 0.9221   |
| No log        | 25.0  | 175  | 0.2055          | 0.9351   |
| No log        | 26.0  | 182  | 0.1982          | 0.9481   |
| No log        | 27.0  | 189  | 0.2105          | 0.9351   |
| No log        | 28.0  | 196  | 0.2204          | 0.9351   |
| No log        | 29.0  | 203  | 0.2095          | 0.9351   |
| No log        | 30.0  | 210  | 0.2107          | 0.9221   |
| No log        | 31.0  | 217  | 0.1808          | 0.9221   |
| No log        | 32.0  | 224  | 0.1711          | 0.9351   |
| No log        | 33.0  | 231  | 0.1777          | 0.9351   |
| No log        | 34.0  | 238  | 0.1700          | 0.9351   |
| No log        | 35.0  | 245  | 0.1743          | 0.9221   |
| No log        | 36.0  | 252  | 0.1877          | 0.9481   |
| No log        | 37.0  | 259  | 0.1855          | 0.9481   |
| No log        | 38.0  | 266  | 0.1792          | 0.9481   |
| No log        | 39.0  | 273  | 0.1607          | 0.9481   |
| No log        | 40.0  | 280  | 0.1681          | 0.9481   |
| No log        | 41.0  | 287  | 0.1768          | 0.9481   |
| No log        | 42.0  | 294  | 0.1909          | 0.9481   |
| No log        | 43.0  | 301  | 0.1812          | 0.9481   |
| No log        | 44.0  | 308  | 0.1822          | 0.9481   |
| No log        | 45.0  | 315  | 0.1731          | 0.9481   |
| No log        | 46.0  | 322  | 0.1846          | 0.9351   |
| No log        | 47.0  | 329  | 0.1846          | 0.9481   |
| No log        | 48.0  | 336  | 0.1915          | 0.9351   |
| No log        | 49.0  | 343  | 0.1879          | 0.9351   |
| No log        | 50.0  | 350  | 0.1860          | 0.9351   |
| No log        | 51.0  | 357  | 0.1907          | 0.9351   |
| No log        | 52.0  | 364  | 0.1729          | 0.9481   |
| No log        | 53.0  | 371  | 0.1837          | 0.9351   |
| No log        | 54.0  | 378  | 0.1793          | 0.9351   |
| No log        | 55.0  | 385  | 0.1783          | 0.9481   |
| No log        | 56.0  | 392  | 0.1844          | 0.9351   |
| No log        | 57.0  | 399  | 0.1724          | 0.9351   |
| No log        | 58.0  | 406  | 0.1819          | 0.9351   |
| No log        | 59.0  | 413  | 0.1792          | 0.9351   |
| No log        | 60.0  | 420  | 0.1695          | 0.9481   |


### Framework versions

- Transformers 4.38.1
- Pytorch 1.10.0+cu111
- Datasets 2.17.1
- Tokenizers 0.15.2