---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: deit-tiny-patch16-224-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: 0.7899543378995434
---

<!-- 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. -->

# deit-tiny-patch16-224-finetuned-piid

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5695
- Accuracy: 0.7900

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2584        | 0.98  | 20   | 1.1962          | 0.4064   |
| 0.7575        | 2.0   | 41   | 0.8537          | 0.6347   |
| 0.6732        | 2.98  | 61   | 0.7349          | 0.6758   |
| 0.5892        | 4.0   | 82   | 0.6902          | 0.7032   |
| 0.5785        | 4.98  | 102  | 0.6303          | 0.7352   |
| 0.4276        | 6.0   | 123  | 0.5948          | 0.7397   |
| 0.3684        | 6.98  | 143  | 0.6197          | 0.7260   |
| 0.3669        | 8.0   | 164  | 0.5451          | 0.7580   |
| 0.3391        | 8.98  | 184  | 0.6707          | 0.7352   |
| 0.3359        | 10.0  | 205  | 0.5079          | 0.8082   |
| 0.3417        | 10.98 | 225  | 0.5678          | 0.7580   |
| 0.2714        | 12.0  | 246  | 0.5774          | 0.7443   |
| 0.3166        | 12.98 | 266  | 0.5747          | 0.7534   |
| 0.2319        | 14.0  | 287  | 0.5598          | 0.7945   |
| 0.227         | 14.98 | 307  | 0.5853          | 0.7397   |
| 0.1801        | 16.0  | 328  | 0.6237          | 0.7580   |
| 0.158         | 16.98 | 348  | 0.5609          | 0.7854   |
| 0.199         | 18.0  | 369  | 0.6128          | 0.7443   |
| 0.1407        | 18.98 | 389  | 0.5727          | 0.7900   |
| 0.1787        | 19.51 | 400  | 0.5695          | 0.7900   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1