---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_rms_lr00001_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: 0.7073170731707317
---

<!-- 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_1x_deit_tiny_rms_lr00001_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: 0.8230
- Accuracy: 0.7073

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.1737          | 0.4634   |
| 1.1816        | 2.0   | 12   | 0.8675          | 0.5366   |
| 1.1816        | 3.0   | 18   | 0.8079          | 0.6341   |
| 0.5246        | 4.0   | 24   | 0.8632          | 0.5854   |
| 0.2225        | 5.0   | 30   | 0.7815          | 0.5610   |
| 0.2225        | 6.0   | 36   | 0.6787          | 0.6585   |
| 0.0792        | 7.0   | 42   | 0.7052          | 0.6585   |
| 0.0792        | 8.0   | 48   | 0.7120          | 0.6341   |
| 0.029         | 9.0   | 54   | 0.8373          | 0.6585   |
| 0.0096        | 10.0  | 60   | 0.6713          | 0.7317   |
| 0.0096        | 11.0  | 66   | 0.7185          | 0.7073   |
| 0.0045        | 12.0  | 72   | 0.7237          | 0.6829   |
| 0.0045        | 13.0  | 78   | 0.7062          | 0.6829   |
| 0.0033        | 14.0  | 84   | 0.7203          | 0.7073   |
| 0.0025        | 15.0  | 90   | 0.7207          | 0.7073   |
| 0.0025        | 16.0  | 96   | 0.7400          | 0.7073   |
| 0.002         | 17.0  | 102  | 0.7337          | 0.6829   |
| 0.002         | 18.0  | 108  | 0.7527          | 0.6829   |
| 0.0017        | 19.0  | 114  | 0.7553          | 0.6829   |
| 0.0015        | 20.0  | 120  | 0.7631          | 0.6829   |
| 0.0015        | 21.0  | 126  | 0.7684          | 0.6829   |
| 0.0014        | 22.0  | 132  | 0.7730          | 0.6829   |
| 0.0014        | 23.0  | 138  | 0.7803          | 0.6829   |
| 0.0012        | 24.0  | 144  | 0.7869          | 0.6829   |
| 0.0011        | 25.0  | 150  | 0.7854          | 0.6829   |
| 0.0011        | 26.0  | 156  | 0.7958          | 0.6829   |
| 0.001         | 27.0  | 162  | 0.7899          | 0.6829   |
| 0.001         | 28.0  | 168  | 0.7956          | 0.6829   |
| 0.001         | 29.0  | 174  | 0.8038          | 0.6829   |
| 0.0009        | 30.0  | 180  | 0.8059          | 0.6829   |
| 0.0009        | 31.0  | 186  | 0.8121          | 0.6829   |
| 0.0008        | 32.0  | 192  | 0.8137          | 0.6829   |
| 0.0008        | 33.0  | 198  | 0.8161          | 0.6829   |
| 0.0008        | 34.0  | 204  | 0.8136          | 0.6829   |
| 0.0008        | 35.0  | 210  | 0.8158          | 0.6829   |
| 0.0008        | 36.0  | 216  | 0.8175          | 0.7073   |
| 0.0007        | 37.0  | 222  | 0.8190          | 0.7073   |
| 0.0007        | 38.0  | 228  | 0.8213          | 0.7073   |
| 0.0007        | 39.0  | 234  | 0.8222          | 0.7073   |
| 0.0007        | 40.0  | 240  | 0.8227          | 0.7073   |
| 0.0007        | 41.0  | 246  | 0.8228          | 0.7073   |
| 0.0007        | 42.0  | 252  | 0.8230          | 0.7073   |
| 0.0007        | 43.0  | 258  | 0.8230          | 0.7073   |
| 0.0007        | 44.0  | 264  | 0.8230          | 0.7073   |
| 0.0007        | 45.0  | 270  | 0.8230          | 0.7073   |
| 0.0007        | 46.0  | 276  | 0.8230          | 0.7073   |
| 0.0007        | 47.0  | 282  | 0.8230          | 0.7073   |
| 0.0007        | 48.0  | 288  | 0.8230          | 0.7073   |
| 0.0007        | 49.0  | 294  | 0.8230          | 0.7073   |
| 0.0007        | 50.0  | 300  | 0.8230          | 0.7073   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1