---
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_fold5
  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: 0.5611608353675075
---

<!-- 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_fold5

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: 3.4928
- Accuracy: 0.5612

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3998        | 1.0   | 924   | 1.5149          | 0.4893   |
| 1.3931        | 2.0   | 1848  | 1.3087          | 0.5424   |
| 1.0339        | 3.0   | 2772  | 1.2795          | 0.5598   |
| 0.6895        | 4.0   | 3696  | 1.2909          | 0.5772   |
| 0.5865        | 5.0   | 4620  | 1.4017          | 0.5644   |
| 0.6353        | 6.0   | 5544  | 1.5191          | 0.5606   |
| 0.4014        | 7.0   | 6468  | 1.6877          | 0.5644   |
| 0.2889        | 8.0   | 7392  | 1.9030          | 0.5601   |
| 0.064         | 9.0   | 8316  | 2.0982          | 0.5633   |
| 0.0342        | 10.0  | 9240  | 2.4199          | 0.5574   |
| 0.071         | 11.0  | 10164 | 2.6790          | 0.5555   |
| 0.0036        | 12.0  | 11088 | 2.8221          | 0.5571   |
| 0.0018        | 13.0  | 12012 | 3.0343          | 0.5609   |
| 0.0019        | 14.0  | 12936 | 3.1489          | 0.5566   |
| 0.0004        | 15.0  | 13860 | 3.2320          | 0.5579   |
| 0.0248        | 16.0  | 14784 | 3.2970          | 0.5595   |
| 0.0003        | 17.0  | 15708 | 3.3641          | 0.5625   |
| 0.0002        | 18.0  | 16632 | 3.4302          | 0.5606   |
| 0.0002        | 19.0  | 17556 | 3.4763          | 0.5620   |
| 0.0001        | 20.0  | 18480 | 3.4928          | 0.5612   |


### Framework versions

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