---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_Adamax_1-e4_20Epoch_Deit-tiny-patch16_fold3
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5695346320346321
---

<!-- 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. -->

# Boya1_Adamax_1-e4_20Epoch_Deit-tiny-patch16_fold3

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: 3.5040
- Accuracy: 0.5695

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3705        | 1.0   | 923   | 1.4925          | 0.4968   |
| 1.1741        | 2.0   | 1846  | 1.3247          | 0.5411   |
| 1.1089        | 3.0   | 2769  | 1.2524          | 0.5777   |
| 0.8912        | 4.0   | 3692  | 1.2699          | 0.5712   |
| 0.6118        | 5.0   | 4615  | 1.3695          | 0.5725   |
| 0.4514        | 6.0   | 5538  | 1.5162          | 0.5690   |
| 0.3342        | 7.0   | 6461  | 1.6732          | 0.5641   |
| 0.1558        | 8.0   | 7384  | 1.8402          | 0.5668   |
| 0.139         | 9.0   | 8307  | 2.0769          | 0.5676   |
| 0.0399        | 10.0  | 9230  | 2.4530          | 0.5582   |
| 0.0251        | 11.0  | 10153 | 2.6195          | 0.5630   |
| 0.0197        | 12.0  | 11076 | 2.8679          | 0.5598   |
| 0.0022        | 13.0  | 11999 | 3.0450          | 0.5593   |
| 0.0102        | 14.0  | 12922 | 3.1628          | 0.5614   |
| 0.0226        | 15.0  | 13845 | 3.2622          | 0.5655   |
| 0.0004        | 16.0  | 14768 | 3.3164          | 0.5668   |
| 0.0003        | 17.0  | 15691 | 3.3759          | 0.5703   |
| 0.0002        | 18.0  | 16614 | 3.4406          | 0.5687   |
| 0.0002        | 19.0  | 17537 | 3.4891          | 0.5695   |
| 0.0004        | 20.0  | 18460 | 3.5040          | 0.5695   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.1.0
- Datasets 2.19.0
- Tokenizers 0.19.1