---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_SGD_1-e3_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: 0.42384823848238484
---

<!-- 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_SGD_1-e3_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: 1.7238
- Accuracy: 0.4238

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4152        | 1.0   | 923   | 2.4593          | 0.2073   |
| 2.4387        | 2.0   | 1846  | 2.2993          | 0.2512   |
| 2.1969        | 3.0   | 2769  | 2.1607          | 0.3133   |
| 2.0455        | 4.0   | 3692  | 2.0589          | 0.3320   |
| 1.8171        | 5.0   | 4615  | 1.9845          | 0.3585   |
| 1.8796        | 6.0   | 5538  | 1.9302          | 0.3656   |
| 1.8281        | 7.0   | 6461  | 1.8840          | 0.3816   |
| 1.7455        | 8.0   | 7384  | 1.8500          | 0.3883   |
| 1.7072        | 9.0   | 8307  | 1.8232          | 0.4003   |
| 1.7401        | 10.0  | 9230  | 1.8005          | 0.4046   |
| 1.8157        | 11.0  | 10153 | 1.7845          | 0.4114   |
| 1.796         | 12.0  | 11076 | 1.7690          | 0.4114   |
| 1.7335        | 13.0  | 11999 | 1.7588          | 0.4122   |
| 1.6292        | 14.0  | 12922 | 1.7473          | 0.4190   |
| 1.7133        | 15.0  | 13845 | 1.7397          | 0.4222   |
| 1.7521        | 16.0  | 14768 | 1.7345          | 0.4195   |
| 1.8322        | 17.0  | 15691 | 1.7291          | 0.4244   |
| 1.7763        | 18.0  | 16614 | 1.7260          | 0.4244   |
| 1.5996        | 19.0  | 17537 | 1.7248          | 0.4225   |
| 1.6259        | 20.0  | 18460 | 1.7238          | 0.4238   |


### Framework versions

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