---
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_fold4
  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: 0.5623306233062331
---

<!-- 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_fold4

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: 3.5379
- Accuracy: 0.5623

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4184        | 1.0   | 923   | 1.5125          | 0.4894   |
| 1.1581        | 2.0   | 1846  | 1.3440          | 0.5398   |
| 1.0675        | 3.0   | 2769  | 1.2921          | 0.5683   |
| 0.9984        | 4.0   | 3692  | 1.3169          | 0.5756   |
| 0.6437        | 5.0   | 4615  | 1.3971          | 0.5629   |
| 0.491         | 6.0   | 5538  | 1.5307          | 0.5547   |
| 0.3697        | 7.0   | 6461  | 1.6679          | 0.5615   |
| 0.2372        | 8.0   | 7384  | 1.9476          | 0.5461   |
| 0.0824        | 9.0   | 8307  | 2.1631          | 0.5531   |
| 0.0471        | 10.0  | 9230  | 2.4822          | 0.5485   |
| 0.0645        | 11.0  | 10153 | 2.7301          | 0.5523   |
| 0.0461        | 12.0  | 11076 | 2.8827          | 0.5588   |
| 0.0021        | 13.0  | 11999 | 3.1615          | 0.5575   |
| 0.0011        | 14.0  | 12922 | 3.1796          | 0.5612   |
| 0.0141        | 15.0  | 13845 | 3.2737          | 0.5566   |
| 0.0004        | 16.0  | 14768 | 3.3570          | 0.5593   |
| 0.0004        | 17.0  | 15691 | 3.4150          | 0.5621   |
| 0.0003        | 18.0  | 16614 | 3.4800          | 0.5615   |
| 0.0002        | 19.0  | 17537 | 3.5180          | 0.5615   |
| 0.0002        | 20.0  | 18460 | 3.5379          | 0.5623   |


### Framework versions

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