---
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_fold4
  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: 0.7619047619047619
---

<!-- 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_fold4

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: 0.6971
- Accuracy: 0.7619

## 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    | 1.1869          | 0.4762   |
| 1.3589        | 2.0   | 12   | 1.4321          | 0.2381   |
| 1.3589        | 3.0   | 18   | 0.8086          | 0.7143   |
| 0.7587        | 4.0   | 24   | 0.7860          | 0.6667   |
| 0.3552        | 5.0   | 30   | 0.6443          | 0.7143   |
| 0.3552        | 6.0   | 36   | 0.6345          | 0.7381   |
| 0.1624        | 7.0   | 42   | 0.6029          | 0.7381   |
| 0.1624        | 8.0   | 48   | 0.6145          | 0.6667   |
| 0.0655        | 9.0   | 54   | 0.6448          | 0.6905   |
| 0.0257        | 10.0  | 60   | 0.6084          | 0.7381   |
| 0.0257        | 11.0  | 66   | 0.5594          | 0.7143   |
| 0.0099        | 12.0  | 72   | 0.6088          | 0.7381   |
| 0.0099        | 13.0  | 78   | 0.6402          | 0.7619   |
| 0.0054        | 14.0  | 84   | 0.6319          | 0.7381   |
| 0.0038        | 15.0  | 90   | 0.6323          | 0.7619   |
| 0.0038        | 16.0  | 96   | 0.6432          | 0.7381   |
| 0.0029        | 17.0  | 102  | 0.6446          | 0.7381   |
| 0.0029        | 18.0  | 108  | 0.6470          | 0.7381   |
| 0.0023        | 19.0  | 114  | 0.6562          | 0.7381   |
| 0.002         | 20.0  | 120  | 0.6656          | 0.7381   |
| 0.002         | 21.0  | 126  | 0.6696          | 0.7381   |
| 0.0017        | 22.0  | 132  | 0.6739          | 0.7381   |
| 0.0017        | 23.0  | 138  | 0.6722          | 0.7619   |
| 0.0015        | 24.0  | 144  | 0.6705          | 0.7619   |
| 0.0014        | 25.0  | 150  | 0.6761          | 0.7619   |
| 0.0014        | 26.0  | 156  | 0.6768          | 0.7619   |
| 0.0012        | 27.0  | 162  | 0.6844          | 0.7619   |
| 0.0012        | 28.0  | 168  | 0.6843          | 0.7619   |
| 0.0012        | 29.0  | 174  | 0.6854          | 0.7619   |
| 0.0011        | 30.0  | 180  | 0.6913          | 0.7619   |
| 0.0011        | 31.0  | 186  | 0.6928          | 0.7619   |
| 0.001         | 32.0  | 192  | 0.6912          | 0.7619   |
| 0.001         | 33.0  | 198  | 0.6912          | 0.7619   |
| 0.001         | 34.0  | 204  | 0.6924          | 0.7619   |
| 0.0009        | 35.0  | 210  | 0.6912          | 0.7619   |
| 0.0009        | 36.0  | 216  | 0.6935          | 0.7619   |
| 0.0009        | 37.0  | 222  | 0.6948          | 0.7619   |
| 0.0009        | 38.0  | 228  | 0.6957          | 0.7619   |
| 0.0009        | 39.0  | 234  | 0.6966          | 0.7619   |
| 0.0009        | 40.0  | 240  | 0.6969          | 0.7619   |
| 0.0009        | 41.0  | 246  | 0.6971          | 0.7619   |
| 0.0009        | 42.0  | 252  | 0.6971          | 0.7619   |
| 0.0009        | 43.0  | 258  | 0.6971          | 0.7619   |
| 0.0008        | 44.0  | 264  | 0.6971          | 0.7619   |
| 0.0009        | 45.0  | 270  | 0.6971          | 0.7619   |
| 0.0009        | 46.0  | 276  | 0.6971          | 0.7619   |
| 0.0008        | 47.0  | 282  | 0.6971          | 0.7619   |
| 0.0008        | 48.0  | 288  | 0.6971          | 0.7619   |
| 0.0009        | 49.0  | 294  | 0.6971          | 0.7619   |
| 0.0009        | 50.0  | 300  | 0.6971          | 0.7619   |


### Framework versions

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