---
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_fold1
  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: 0.5568829758349172
---

<!-- 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_fold1

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: 3.5356
- Accuracy: 0.5569

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3865        | 1.0   | 924   | 1.5601          | 0.4768   |
| 1.2182        | 2.0   | 1848  | 1.4517          | 0.4963   |
| 1.2424        | 3.0   | 2772  | 1.3040          | 0.5531   |
| 0.8291        | 4.0   | 3696  | 1.3092          | 0.5745   |
| 0.6764        | 5.0   | 4620  | 1.3977          | 0.5724   |
| 0.5779        | 6.0   | 5544  | 1.5087          | 0.5601   |
| 0.3166        | 7.0   | 6468  | 1.7036          | 0.5577   |
| 0.2404        | 8.0   | 7392  | 1.9068          | 0.5528   |
| 0.144         | 9.0   | 8316  | 2.1442          | 0.5547   |
| 0.165         | 10.0  | 9240  | 2.4839          | 0.5509   |
| 0.0646        | 11.0  | 10164 | 2.7042          | 0.5490   |
| 0.0029        | 12.0  | 11088 | 2.9034          | 0.5523   |
| 0.0317        | 13.0  | 12012 | 3.1091          | 0.5504   |
| 0.0012        | 14.0  | 12936 | 3.2476          | 0.5496   |
| 0.0008        | 15.0  | 13860 | 3.3162          | 0.5569   |
| 0.0005        | 16.0  | 14784 | 3.3879          | 0.5525   |
| 0.0003        | 17.0  | 15708 | 3.4370          | 0.5517   |
| 0.0007        | 18.0  | 16632 | 3.4907          | 0.5542   |
| 0.0003        | 19.0  | 17556 | 3.5171          | 0.5566   |
| 0.0003        | 20.0  | 18480 | 3.5356          | 0.5569   |


### Framework versions

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