---
license: apache-2.0
base_model: microsoft/cvt-21-384-22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cvt-21-384-22k-finetuned
  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: 1.0
---

<!-- 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-21-384-22k-finetuned

This model is a fine-tuned version of [microsoft/cvt-21-384-22k](https://huggingface.co/microsoft/cvt-21-384-22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0004
- Accuracy: 1.0

## 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: 10
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 90   | 0.1145          | 0.9777   |
| No log        | 2.0   | 180  | 0.0646          | 0.9732   |
| No log        | 3.0   | 270  | 0.0524          | 0.9821   |
| No log        | 4.0   | 360  | 0.0144          | 0.9955   |
| No log        | 5.0   | 450  | 0.0234          | 0.9911   |
| 0.3541        | 6.0   | 540  | 0.0189          | 0.9911   |
| 0.3541        | 7.0   | 630  | 0.0099          | 0.9955   |
| 0.3541        | 8.0   | 720  | 0.0253          | 0.9866   |
| 0.3541        | 9.0   | 810  | 0.0414          | 0.9866   |
| 0.3541        | 10.0  | 900  | 0.0034          | 1.0      |
| 0.3541        | 11.0  | 990  | 0.0099          | 0.9955   |
| 0.2485        | 12.0  | 1080 | 0.0004          | 1.0      |
| 0.2485        | 13.0  | 1170 | 0.0088          | 0.9955   |
| 0.2485        | 14.0  | 1260 | 0.0104          | 0.9955   |
| 0.2485        | 15.0  | 1350 | 0.0001          | 1.0      |
| 0.2485        | 16.0  | 1440 | 0.0098          | 0.9955   |
| 0.2229        | 17.0  | 1530 | 0.0002          | 1.0      |
| 0.2229        | 18.0  | 1620 | 0.0004          | 1.0      |
| 0.2229        | 19.0  | 1710 | 0.0002          | 1.0      |
| 0.2229        | 20.0  | 1800 | 0.0001          | 1.0      |
| 0.2229        | 21.0  | 1890 | 0.0005          | 1.0      |
| 0.2229        | 22.0  | 1980 | 0.0002          | 1.0      |
| 0.2192        | 23.0  | 2070 | 0.0006          | 1.0      |
| 0.2192        | 24.0  | 2160 | 0.0001          | 1.0      |
| 0.2192        | 25.0  | 2250 | 0.0013          | 1.0      |
| 0.2192        | 26.0  | 2340 | 0.0002          | 1.0      |
| 0.2192        | 27.0  | 2430 | 0.0002          | 1.0      |
| 0.211         | 28.0  | 2520 | 0.0012          | 1.0      |
| 0.211         | 29.0  | 2610 | 0.0013          | 1.0      |
| 0.211         | 30.0  | 2700 | 0.0004          | 1.0      |


### Framework versions

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