---
license: apache-2.0
base_model: facebook/convnext-small-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-small-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: 0.7625570776255708
---

<!-- 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. -->

# convnext-small-224-finetuned-piid

This model is a fine-tuned version of [facebook/convnext-small-224](https://huggingface.co/facebook/convnext-small-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5651
- Accuracy: 0.7626

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3405        | 0.98  | 20   | 1.3201          | 0.4155   |
| 1.1715        | 2.0   | 41   | 1.1362          | 0.5708   |
| 0.9231        | 2.98  | 61   | 0.9255          | 0.6438   |
| 0.7128        | 4.0   | 82   | 0.7558          | 0.6986   |
| 0.6204        | 4.98  | 102  | 0.7056          | 0.7534   |
| 0.5322        | 6.0   | 123  | 0.6610          | 0.7397   |
| 0.4403        | 6.98  | 143  | 0.6639          | 0.7443   |
| 0.4388        | 8.0   | 164  | 0.6472          | 0.7306   |
| 0.3901        | 8.98  | 184  | 0.6684          | 0.7352   |
| 0.4202        | 10.0  | 205  | 0.5934          | 0.7397   |
| 0.3784        | 10.98 | 225  | 0.5651          | 0.7626   |
| 0.2973        | 12.0  | 246  | 0.6439          | 0.7580   |
| 0.3614        | 12.98 | 266  | 0.5844          | 0.7534   |
| 0.2795        | 14.0  | 287  | 0.6015          | 0.7306   |
| 0.2825        | 14.98 | 307  | 0.6031          | 0.7626   |
| 0.2364        | 16.0  | 328  | 0.6249          | 0.7534   |
| 0.2162        | 16.98 | 348  | 0.6248          | 0.7626   |
| 0.2455        | 18.0  | 369  | 0.6153          | 0.7489   |
| 0.2314        | 18.98 | 389  | 0.6113          | 0.7580   |
| 0.248         | 19.51 | 400  | 0.6131          | 0.7580   |


### Framework versions

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