---
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-PinnatelyCompound
  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: 0.9955357142857143
---

<!-- 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-PinnatelyCompound

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: 0.0064
- Accuracy: 0.9955

## 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: 40
- eval_batch_size: 16
- 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   | 23   | 0.2918          | 0.8973   |
| No log        | 2.0   | 46   | 0.1656          | 0.9330   |
| No log        | 3.0   | 69   | 0.0529          | 0.9821   |
| No log        | 4.0   | 92   | 0.0144          | 0.9955   |
| No log        | 5.0   | 115  | 0.0266          | 0.9911   |
| No log        | 6.0   | 138  | 0.0244          | 0.9955   |
| No log        | 7.0   | 161  | 0.0144          | 0.9955   |
| No log        | 8.0   | 184  | 0.0154          | 0.9955   |
| No log        | 9.0   | 207  | 0.0188          | 0.9911   |
| No log        | 10.0  | 230  | 0.0094          | 0.9955   |
| No log        | 11.0  | 253  | 0.0055          | 1.0      |
| No log        | 12.0  | 276  | 0.0026          | 1.0      |
| No log        | 13.0  | 299  | 0.0057          | 1.0      |
| No log        | 14.0  | 322  | 0.0079          | 0.9955   |
| No log        | 15.0  | 345  | 0.0026          | 1.0      |
| No log        | 16.0  | 368  | 0.0017          | 1.0      |
| No log        | 17.0  | 391  | 0.0044          | 0.9955   |
| No log        | 18.0  | 414  | 0.0038          | 1.0      |
| No log        | 19.0  | 437  | 0.0120          | 0.9911   |
| No log        | 20.0  | 460  | 0.0005          | 1.0      |
| No log        | 21.0  | 483  | 0.0019          | 1.0      |
| 0.2553        | 22.0  | 506  | 0.0020          | 1.0      |
| 0.2553        | 23.0  | 529  | 0.0026          | 1.0      |
| 0.2553        | 24.0  | 552  | 0.0053          | 0.9955   |
| 0.2553        | 25.0  | 575  | 0.0009          | 1.0      |
| 0.2553        | 26.0  | 598  | 0.0008          | 1.0      |
| 0.2553        | 27.0  | 621  | 0.0016          | 1.0      |
| 0.2553        | 28.0  | 644  | 0.0010          | 1.0      |
| 0.2553        | 29.0  | 667  | 0.0008          | 1.0      |
| 0.2553        | 30.0  | 690  | 0.0064          | 0.9955   |


### Framework versions

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