---
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_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: 0.42884199134199136
---

<!-- 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_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: 1.7155
- Accuracy: 0.4288

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4106        | 1.0   | 923   | 2.4578          | 0.2002   |
| 2.3587        | 2.0   | 1846  | 2.2972          | 0.2516   |
| 2.1274        | 3.0   | 2769  | 2.1627          | 0.3055   |
| 2.1583        | 4.0   | 3692  | 2.0604          | 0.3279   |
| 1.9036        | 5.0   | 4615  | 1.9842          | 0.3458   |
| 1.7721        | 6.0   | 5538  | 1.9243          | 0.3582   |
| 1.9867        | 7.0   | 6461  | 1.8782          | 0.3726   |
| 1.8532        | 8.0   | 7384  | 1.8428          | 0.3891   |
| 1.8503        | 9.0   | 8307  | 1.8165          | 0.4004   |
| 1.79          | 10.0  | 9230  | 1.7943          | 0.4037   |
| 1.7717        | 11.0  | 10153 | 1.7761          | 0.4091   |
| 1.7696        | 12.0  | 11076 | 1.7613          | 0.4148   |
| 1.7298        | 13.0  | 11999 | 1.7507          | 0.4191   |
| 1.7468        | 14.0  | 12922 | 1.7401          | 0.4210   |
| 1.6085        | 15.0  | 13845 | 1.7322          | 0.4229   |
| 1.7188        | 16.0  | 14768 | 1.7257          | 0.4278   |
| 1.7307        | 17.0  | 15691 | 1.7212          | 0.4259   |
| 1.5257        | 18.0  | 16614 | 1.7177          | 0.4275   |
| 1.6729        | 19.0  | 17537 | 1.7160          | 0.4294   |
| 1.7293        | 20.0  | 18460 | 1.7155          | 0.4288   |


### Framework versions

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