---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_Adamax_1-e4_20Epoch_Deit-small-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: 0.6046701058919359
---

<!-- 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-small-patch16_fold1

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: 3.6631
- Accuracy: 0.6047

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2053        | 1.0   | 924   | 1.3479          | 0.5436   |
| 1.0533        | 2.0   | 1848  | 1.2465          | 0.5745   |
| 0.9598        | 3.0   | 2772  | 1.2623          | 0.5786   |
| 0.5046        | 4.0   | 3696  | 1.2915          | 0.5987   |
| 0.3319        | 5.0   | 4620  | 1.4822          | 0.5906   |
| 0.2366        | 6.0   | 5544  | 1.7116          | 0.5854   |
| 0.0946        | 7.0   | 6468  | 2.0587          | 0.5873   |
| 0.0513        | 8.0   | 7392  | 2.3576          | 0.5971   |
| 0.0119        | 9.0   | 8316  | 2.5882          | 0.5916   |
| 0.005         | 10.0  | 9240  | 2.8824          | 0.5900   |
| 0.0005        | 11.0  | 10164 | 2.9269          | 0.6036   |
| 0.0002        | 12.0  | 11088 | 3.1123          | 0.5979   |
| 0.002         | 13.0  | 12012 | 3.1469          | 0.5965   |
| 0.0001        | 14.0  | 12936 | 3.1949          | 0.6009   |
| 0.0001        | 15.0  | 13860 | 3.2471          | 0.6033   |
| 0.0           | 16.0  | 14784 | 3.3448          | 0.6036   |
| 0.0           | 17.0  | 15708 | 3.4378          | 0.6047   |
| 0.0           | 18.0  | 16632 | 3.5318          | 0.6047   |
| 0.0           | 19.0  | 17556 | 3.6207          | 0.6041   |
| 0.0           | 20.0  | 18480 | 3.6631          | 0.6047   |


### Framework versions

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