---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-22k-224-finetuned-piid
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: val
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7853881278538812
---

<!-- 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. -->

# convnextv2-tiny-22k-224-finetuned-piid

This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-224](https://huggingface.co/facebook/convnextv2-tiny-22k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6118
- Accuracy: 0.7854

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2083        | 0.98  | 20   | 1.0137          | 0.6027   |
| 0.6826        | 2.0   | 41   | 0.6901          | 0.6895   |
| 0.5161        | 2.98  | 61   | 0.6377          | 0.7078   |
| 0.4475        | 4.0   | 82   | 0.5423          | 0.7215   |
| 0.4325        | 4.98  | 102  | 0.5165          | 0.7671   |
| 0.3433        | 6.0   | 123  | 0.5916          | 0.7763   |
| 0.2677        | 6.98  | 143  | 0.5866          | 0.7534   |
| 0.2498        | 8.0   | 164  | 0.5146          | 0.7900   |
| 0.2387        | 8.98  | 184  | 0.5631          | 0.7580   |
| 0.2132        | 10.0  | 205  | 0.5320          | 0.7991   |
| 0.2178        | 10.98 | 225  | 0.5833          | 0.7854   |
| 0.1474        | 12.0  | 246  | 0.5902          | 0.7900   |
| 0.1627        | 12.98 | 266  | 0.6142          | 0.7808   |
| 0.1651        | 14.0  | 287  | 0.6063          | 0.7808   |
| 0.158         | 14.98 | 307  | 0.6130          | 0.7808   |
| 0.126         | 16.0  | 328  | 0.6647          | 0.7671   |
| 0.0821        | 16.98 | 348  | 0.5972          | 0.7808   |
| 0.1062        | 18.0  | 369  | 0.5975          | 0.7945   |
| 0.1031        | 18.98 | 389  | 0.6129          | 0.7808   |
| 0.1268        | 19.51 | 400  | 0.6118          | 0.7854   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3