---
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_sgd_001_fold2
  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: 0.17777777777777778
---

<!-- 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_sgd_001_fold2

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: 1.4913
- Accuracy: 0.1778

## 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: 0.001
- 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    | 1.6461          | 0.2222   |
| 1.647         | 2.0   | 12   | 1.5827          | 0.2      |
| 1.647         | 3.0   | 18   | 1.5400          | 0.2      |
| 1.5111        | 4.0   | 24   | 1.5101          | 0.2      |
| 1.4472        | 5.0   | 30   | 1.4855          | 0.1778   |
| 1.4472        | 6.0   | 36   | 1.4711          | 0.1778   |
| 1.3765        | 7.0   | 42   | 1.4618          | 0.2      |
| 1.3765        | 8.0   | 48   | 1.4555          | 0.2      |
| 1.3363        | 9.0   | 54   | 1.4523          | 0.2222   |
| 1.3131        | 10.0  | 60   | 1.4505          | 0.2      |
| 1.3131        | 11.0  | 66   | 1.4495          | 0.2      |
| 1.2743        | 12.0  | 72   | 1.4504          | 0.2      |
| 1.2743        | 13.0  | 78   | 1.4505          | 0.2      |
| 1.2923        | 14.0  | 84   | 1.4516          | 0.2      |
| 1.2475        | 15.0  | 90   | 1.4529          | 0.2      |
| 1.2475        | 16.0  | 96   | 1.4558          | 0.2      |
| 1.2052        | 17.0  | 102  | 1.4591          | 0.1778   |
| 1.2052        | 18.0  | 108  | 1.4603          | 0.1778   |
| 1.2375        | 19.0  | 114  | 1.4628          | 0.1778   |
| 1.1665        | 20.0  | 120  | 1.4654          | 0.1778   |
| 1.1665        | 21.0  | 126  | 1.4668          | 0.1778   |
| 1.1508        | 22.0  | 132  | 1.4681          | 0.1778   |
| 1.1508        | 23.0  | 138  | 1.4710          | 0.1778   |
| 1.1615        | 24.0  | 144  | 1.4735          | 0.1778   |
| 1.1372        | 25.0  | 150  | 1.4742          | 0.1778   |
| 1.1372        | 26.0  | 156  | 1.4775          | 0.1778   |
| 1.1389        | 27.0  | 162  | 1.4787          | 0.1778   |
| 1.1389        | 28.0  | 168  | 1.4813          | 0.1778   |
| 1.1191        | 29.0  | 174  | 1.4821          | 0.1778   |
| 1.106         | 30.0  | 180  | 1.4844          | 0.1778   |
| 1.106         | 31.0  | 186  | 1.4853          | 0.1778   |
| 1.1156        | 32.0  | 192  | 1.4867          | 0.1778   |
| 1.1156        | 33.0  | 198  | 1.4872          | 0.1778   |
| 1.127         | 34.0  | 204  | 1.4879          | 0.1778   |
| 1.1055        | 35.0  | 210  | 1.4887          | 0.1778   |
| 1.1055        | 36.0  | 216  | 1.4895          | 0.1778   |
| 1.089         | 37.0  | 222  | 1.4902          | 0.1778   |
| 1.089         | 38.0  | 228  | 1.4907          | 0.1778   |
| 1.0605        | 39.0  | 234  | 1.4911          | 0.1778   |
| 1.0925        | 40.0  | 240  | 1.4913          | 0.1778   |
| 1.0925        | 41.0  | 246  | 1.4913          | 0.1778   |
| 1.1025        | 42.0  | 252  | 1.4913          | 0.1778   |
| 1.1025        | 43.0  | 258  | 1.4913          | 0.1778   |
| 1.1085        | 44.0  | 264  | 1.4913          | 0.1778   |
| 1.0909        | 45.0  | 270  | 1.4913          | 0.1778   |
| 1.0909        | 46.0  | 276  | 1.4913          | 0.1778   |
| 1.0889        | 47.0  | 282  | 1.4913          | 0.1778   |
| 1.0889        | 48.0  | 288  | 1.4913          | 0.1778   |
| 1.0611        | 49.0  | 294  | 1.4913          | 0.1778   |
| 1.1045        | 50.0  | 300  | 1.4913          | 0.1778   |


### Framework versions

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