---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_tiny_rms_0001_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: 0.813953488372093
---

<!-- 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. -->

# hushem_40x_deit_tiny_rms_0001_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: 1.8398
- Accuracy: 0.8140

## 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: 32
- eval_batch_size: 32
- 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: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1282        | 1.0   | 217   | 0.8975          | 0.8372   |
| 0.0209        | 2.0   | 434   | 0.8245          | 0.7674   |
| 0.0218        | 3.0   | 651   | 0.3670          | 0.9302   |
| 0.0205        | 4.0   | 868   | 1.2586          | 0.8372   |
| 0.0008        | 5.0   | 1085  | 0.8797          | 0.7907   |
| 0.0606        | 6.0   | 1302  | 1.1984          | 0.8605   |
| 0.1313        | 7.0   | 1519  | 1.3827          | 0.8372   |
| 0.0283        | 8.0   | 1736  | 0.8068          | 0.8605   |
| 0.0037        | 9.0   | 1953  | 1.0055          | 0.8837   |
| 0.0058        | 10.0  | 2170  | 1.7904          | 0.8140   |
| 0.0074        | 11.0  | 2387  | 1.3591          | 0.8140   |
| 0.0197        | 12.0  | 2604  | 1.3843          | 0.8605   |
| 0.0           | 13.0  | 2821  | 1.1075          | 0.8837   |
| 0.0155        | 14.0  | 3038  | 1.0442          | 0.8837   |
| 0.0002        | 15.0  | 3255  | 1.5088          | 0.8605   |
| 0.0288        | 16.0  | 3472  | 0.6806          | 0.8605   |
| 0.0057        | 17.0  | 3689  | 0.9450          | 0.8837   |
| 0.0           | 18.0  | 3906  | 1.1935          | 0.8372   |
| 0.0           | 19.0  | 4123  | 1.2605          | 0.8605   |
| 0.0           | 20.0  | 4340  | 1.0286          | 0.8140   |
| 0.0001        | 21.0  | 4557  | 0.9245          | 0.8605   |
| 0.0039        | 22.0  | 4774  | 1.3627          | 0.8372   |
| 0.0           | 23.0  | 4991  | 1.4994          | 0.8605   |
| 0.0001        | 24.0  | 5208  | 1.2134          | 0.7907   |
| 0.0001        | 25.0  | 5425  | 1.0301          | 0.8372   |
| 0.0           | 26.0  | 5642  | 1.0457          | 0.8837   |
| 0.0           | 27.0  | 5859  | 1.2728          | 0.8140   |
| 0.0           | 28.0  | 6076  | 1.0821          | 0.8837   |
| 0.0           | 29.0  | 6293  | 1.1243          | 0.8837   |
| 0.0           | 30.0  | 6510  | 1.1728          | 0.8837   |
| 0.0           | 31.0  | 6727  | 1.2386          | 0.8605   |
| 0.0           | 32.0  | 6944  | 1.3089          | 0.8605   |
| 0.0           | 33.0  | 7161  | 1.3713          | 0.8605   |
| 0.0           | 34.0  | 7378  | 1.4458          | 0.8605   |
| 0.0           | 35.0  | 7595  | 1.5096          | 0.8605   |
| 0.0           | 36.0  | 7812  | 1.5439          | 0.8605   |
| 0.0           | 37.0  | 8029  | 1.5992          | 0.8605   |
| 0.0           | 38.0  | 8246  | 1.6228          | 0.8605   |
| 0.0           | 39.0  | 8463  | 1.6686          | 0.8372   |
| 0.0           | 40.0  | 8680  | 1.7133          | 0.8372   |
| 0.0           | 41.0  | 8897  | 1.7502          | 0.8372   |
| 0.0           | 42.0  | 9114  | 1.7750          | 0.8372   |
| 0.0           | 43.0  | 9331  | 1.7947          | 0.8372   |
| 0.0           | 44.0  | 9548  | 1.8093          | 0.8372   |
| 0.0           | 45.0  | 9765  | 1.8201          | 0.8372   |
| 0.0           | 46.0  | 9982  | 1.8280          | 0.8372   |
| 0.0           | 47.0  | 10199 | 1.8337          | 0.8372   |
| 0.0           | 48.0  | 10416 | 1.8373          | 0.8372   |
| 0.0           | 49.0  | 10633 | 1.8394          | 0.8372   |
| 0.0           | 50.0  | 10850 | 1.8398          | 0.8140   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2