---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: deit-tiny-patch16-224-finetuned-main-gpu-20e-final
  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: 0.9856292517006803
---

<!-- 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-main-gpu-20e-final

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: 0.0420
- Accuracy: 0.9856

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6047        | 1.0   | 551   | 0.6283          | 0.7111   |
| 0.431         | 2.0   | 1102  | 0.3962          | 0.8366   |
| 0.352         | 3.0   | 1653  | 0.2620          | 0.8953   |
| 0.2682        | 4.0   | 2204  | 0.1814          | 0.9318   |
| 0.2533        | 5.0   | 2755  | 0.1564          | 0.9396   |
| 0.2069        | 6.0   | 3306  | 0.1243          | 0.9531   |
| 0.2065        | 7.0   | 3857  | 0.1048          | 0.9603   |
| 0.194         | 8.0   | 4408  | 0.1019          | 0.9636   |
| 0.1879        | 9.0   | 4959  | 0.0877          | 0.9671   |
| 0.1584        | 10.0  | 5510  | 0.0870          | 0.9687   |
| 0.1426        | 11.0  | 6061  | 0.0814          | 0.9718   |
| 0.1596        | 12.0  | 6612  | 0.0740          | 0.9749   |
| 0.1125        | 13.0  | 7163  | 0.0613          | 0.9781   |
| 0.1374        | 14.0  | 7714  | 0.0570          | 0.9787   |
| 0.1003        | 15.0  | 8265  | 0.0596          | 0.9793   |
| 0.109         | 16.0  | 8816  | 0.0511          | 0.9815   |
| 0.1206        | 17.0  | 9367  | 0.0497          | 0.9829   |
| 0.1024        | 18.0  | 9918  | 0.0437          | 0.9844   |
| 0.1051        | 19.0  | 10469 | 0.0420          | 0.9851   |
| 0.0955        | 20.0  | 11020 | 0.0420          | 0.9856   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2