---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: deit-small-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: 0.7671232876712328
---

<!-- 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-small-patch16-224-finetuned-piid

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6202
- Accuracy: 0.7671

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1537        | 0.98  | 20   | 1.0005          | 0.5479   |
| 0.7025        | 2.0   | 41   | 0.8481          | 0.5936   |
| 0.6581        | 2.98  | 61   | 0.6351          | 0.7215   |
| 0.5019        | 4.0   | 82   | 0.6696          | 0.7215   |
| 0.4708        | 4.98  | 102  | 0.5861          | 0.7534   |
| 0.3647        | 6.0   | 123  | 0.5584          | 0.7763   |
| 0.2973        | 6.98  | 143  | 0.5784          | 0.7671   |
| 0.2827        | 8.0   | 164  | 0.5851          | 0.7671   |
| 0.237         | 8.98  | 184  | 0.6791          | 0.7626   |
| 0.2505        | 10.0  | 205  | 0.5550          | 0.7626   |
| 0.2018        | 10.98 | 225  | 0.5446          | 0.7626   |
| 0.1841        | 12.0  | 246  | 0.5497          | 0.7443   |
| 0.1692        | 12.98 | 266  | 0.5917          | 0.7717   |
| 0.1624        | 14.0  | 287  | 0.5254          | 0.7763   |
| 0.1518        | 14.98 | 307  | 0.5296          | 0.7808   |
| 0.1275        | 16.0  | 328  | 0.5858          | 0.7626   |
| 0.1107        | 16.98 | 348  | 0.5919          | 0.7763   |
| 0.1192        | 18.0  | 369  | 0.6027          | 0.7717   |
| 0.0842        | 18.98 | 389  | 0.6435          | 0.7717   |
| 0.1472        | 19.51 | 400  | 0.6202          | 0.7671   |


### Framework versions

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