---
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_00001_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: 0.7674418604651163
---

<!-- 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_00001_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: 0.6755
- Accuracy: 0.7674

## 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    | 1.2450          | 0.3953   |
| 1.3266        | 2.0   | 12   | 1.0282          | 0.4884   |
| 1.3266        | 3.0   | 18   | 0.8766          | 0.6512   |
| 0.6113        | 4.0   | 24   | 0.8143          | 0.6279   |
| 0.301         | 5.0   | 30   | 0.9703          | 0.6047   |
| 0.301         | 6.0   | 36   | 0.7894          | 0.7209   |
| 0.1194        | 7.0   | 42   | 0.8712          | 0.6512   |
| 0.1194        | 8.0   | 48   | 0.7416          | 0.6744   |
| 0.0478        | 9.0   | 54   | 0.7289          | 0.6744   |
| 0.0192        | 10.0  | 60   | 0.6181          | 0.7209   |
| 0.0192        | 11.0  | 66   | 0.7194          | 0.6977   |
| 0.007         | 12.0  | 72   | 0.6519          | 0.6744   |
| 0.007         | 13.0  | 78   | 0.6428          | 0.7209   |
| 0.0038        | 14.0  | 84   | 0.6323          | 0.6977   |
| 0.0027        | 15.0  | 90   | 0.6303          | 0.7209   |
| 0.0027        | 16.0  | 96   | 0.6496          | 0.7209   |
| 0.0021        | 17.0  | 102  | 0.6367          | 0.7209   |
| 0.0021        | 18.0  | 108  | 0.6386          | 0.7209   |
| 0.0018        | 19.0  | 114  | 0.6562          | 0.7442   |
| 0.0015        | 20.0  | 120  | 0.6541          | 0.7442   |
| 0.0015        | 21.0  | 126  | 0.6493          | 0.7442   |
| 0.0014        | 22.0  | 132  | 0.6669          | 0.7442   |
| 0.0014        | 23.0  | 138  | 0.6543          | 0.7674   |
| 0.0012        | 24.0  | 144  | 0.6581          | 0.7442   |
| 0.0011        | 25.0  | 150  | 0.6534          | 0.7442   |
| 0.0011        | 26.0  | 156  | 0.6644          | 0.7442   |
| 0.001         | 27.0  | 162  | 0.6622          | 0.7674   |
| 0.001         | 28.0  | 168  | 0.6583          | 0.7442   |
| 0.001         | 29.0  | 174  | 0.6594          | 0.7674   |
| 0.0009        | 30.0  | 180  | 0.6672          | 0.7674   |
| 0.0009        | 31.0  | 186  | 0.6681          | 0.7674   |
| 0.0008        | 32.0  | 192  | 0.6656          | 0.7674   |
| 0.0008        | 33.0  | 198  | 0.6699          | 0.7674   |
| 0.0008        | 34.0  | 204  | 0.6718          | 0.7674   |
| 0.0008        | 35.0  | 210  | 0.6718          | 0.7674   |
| 0.0008        | 36.0  | 216  | 0.6735          | 0.7674   |
| 0.0008        | 37.0  | 222  | 0.6740          | 0.7674   |
| 0.0008        | 38.0  | 228  | 0.6754          | 0.7674   |
| 0.0007        | 39.0  | 234  | 0.6750          | 0.7674   |
| 0.0007        | 40.0  | 240  | 0.6751          | 0.7674   |
| 0.0007        | 41.0  | 246  | 0.6753          | 0.7674   |
| 0.0007        | 42.0  | 252  | 0.6755          | 0.7674   |
| 0.0007        | 43.0  | 258  | 0.6755          | 0.7674   |
| 0.0007        | 44.0  | 264  | 0.6755          | 0.7674   |
| 0.0007        | 45.0  | 270  | 0.6755          | 0.7674   |
| 0.0007        | 46.0  | 276  | 0.6755          | 0.7674   |
| 0.0007        | 47.0  | 282  | 0.6755          | 0.7674   |
| 0.0007        | 48.0  | 288  | 0.6755          | 0.7674   |
| 0.0007        | 49.0  | 294  | 0.6755          | 0.7674   |
| 0.0007        | 50.0  | 300  | 0.6755          | 0.7674   |


### Framework versions

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