---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_base_sgd_001_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: 0.35714285714285715
---

<!-- 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_base_sgd_001_fold4

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3500
- Accuracy: 0.3571

## 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    | 1.4099          | 0.1667   |
| 1.4464        | 2.0   | 12   | 1.4056          | 0.1667   |
| 1.4464        | 3.0   | 18   | 1.4012          | 0.1667   |
| 1.409         | 4.0   | 24   | 1.3971          | 0.1667   |
| 1.405         | 5.0   | 30   | 1.3937          | 0.1905   |
| 1.405         | 6.0   | 36   | 1.3906          | 0.1905   |
| 1.3913        | 7.0   | 42   | 1.3880          | 0.1905   |
| 1.3913        | 8.0   | 48   | 1.3852          | 0.1905   |
| 1.3821        | 9.0   | 54   | 1.3824          | 0.1667   |
| 1.3709        | 10.0  | 60   | 1.3801          | 0.1667   |
| 1.3709        | 11.0  | 66   | 1.3778          | 0.1905   |
| 1.3643        | 12.0  | 72   | 1.3757          | 0.2143   |
| 1.3643        | 13.0  | 78   | 1.3738          | 0.2619   |
| 1.3452        | 14.0  | 84   | 1.3719          | 0.2619   |
| 1.3451        | 15.0  | 90   | 1.3702          | 0.2619   |
| 1.3451        | 16.0  | 96   | 1.3686          | 0.2619   |
| 1.3306        | 17.0  | 102  | 1.3669          | 0.2619   |
| 1.3306        | 18.0  | 108  | 1.3655          | 0.2857   |
| 1.3266        | 19.0  | 114  | 1.3643          | 0.2857   |
| 1.3291        | 20.0  | 120  | 1.3632          | 0.2857   |
| 1.3291        | 21.0  | 126  | 1.3620          | 0.2857   |
| 1.3218        | 22.0  | 132  | 1.3610          | 0.2857   |
| 1.3218        | 23.0  | 138  | 1.3598          | 0.3095   |
| 1.3151        | 24.0  | 144  | 1.3588          | 0.3333   |
| 1.3182        | 25.0  | 150  | 1.3578          | 0.3333   |
| 1.3182        | 26.0  | 156  | 1.3568          | 0.3333   |
| 1.3072        | 27.0  | 162  | 1.3559          | 0.3333   |
| 1.3072        | 28.0  | 168  | 1.3552          | 0.3333   |
| 1.3081        | 29.0  | 174  | 1.3545          | 0.3571   |
| 1.3087        | 30.0  | 180  | 1.3539          | 0.3571   |
| 1.3087        | 31.0  | 186  | 1.3532          | 0.3571   |
| 1.2983        | 32.0  | 192  | 1.3527          | 0.3571   |
| 1.2983        | 33.0  | 198  | 1.3521          | 0.3333   |
| 1.2931        | 34.0  | 204  | 1.3516          | 0.3571   |
| 1.2999        | 35.0  | 210  | 1.3512          | 0.3571   |
| 1.2999        | 36.0  | 216  | 1.3509          | 0.3571   |
| 1.2926        | 37.0  | 222  | 1.3506          | 0.3571   |
| 1.2926        | 38.0  | 228  | 1.3504          | 0.3571   |
| 1.2948        | 39.0  | 234  | 1.3502          | 0.3571   |
| 1.2828        | 40.0  | 240  | 1.3501          | 0.3571   |
| 1.2828        | 41.0  | 246  | 1.3500          | 0.3571   |
| 1.2878        | 42.0  | 252  | 1.3500          | 0.3571   |
| 1.2878        | 43.0  | 258  | 1.3500          | 0.3571   |
| 1.2878        | 44.0  | 264  | 1.3500          | 0.3571   |
| 1.2935        | 45.0  | 270  | 1.3500          | 0.3571   |
| 1.2935        | 46.0  | 276  | 1.3500          | 0.3571   |
| 1.289         | 47.0  | 282  | 1.3500          | 0.3571   |
| 1.289         | 48.0  | 288  | 1.3500          | 0.3571   |
| 1.2878        | 49.0  | 294  | 1.3500          | 0.3571   |
| 1.2975        | 50.0  | 300  | 1.3500          | 0.3571   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0