---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_small_sgd_001_fold1
  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: 0.4666666666666667
---

<!-- 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_small_sgd_001_fold1

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2536
- Accuracy: 0.4667

## 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    | 1.3733          | 0.3778   |
| 1.5546        | 2.0   | 12   | 1.3601          | 0.4      |
| 1.5546        | 3.0   | 18   | 1.3490          | 0.4222   |
| 1.5316        | 4.0   | 24   | 1.3414          | 0.4222   |
| 1.4864        | 5.0   | 30   | 1.3332          | 0.4222   |
| 1.4864        | 6.0   | 36   | 1.3258          | 0.4222   |
| 1.4723        | 7.0   | 42   | 1.3198          | 0.4222   |
| 1.4723        | 8.0   | 48   | 1.3148          | 0.4      |
| 1.4485        | 9.0   | 54   | 1.3096          | 0.4      |
| 1.4339        | 10.0  | 60   | 1.3042          | 0.4      |
| 1.4339        | 11.0  | 66   | 1.3005          | 0.4222   |
| 1.4182        | 12.0  | 72   | 1.2965          | 0.4222   |
| 1.4182        | 13.0  | 78   | 1.2931          | 0.4      |
| 1.3944        | 14.0  | 84   | 1.2902          | 0.4222   |
| 1.3955        | 15.0  | 90   | 1.2868          | 0.4444   |
| 1.3955        | 16.0  | 96   | 1.2841          | 0.4444   |
| 1.3685        | 17.0  | 102  | 1.2813          | 0.4444   |
| 1.3685        | 18.0  | 108  | 1.2791          | 0.4444   |
| 1.351         | 19.0  | 114  | 1.2769          | 0.4444   |
| 1.3583        | 20.0  | 120  | 1.2750          | 0.4667   |
| 1.3583        | 21.0  | 126  | 1.2734          | 0.4444   |
| 1.3432        | 22.0  | 132  | 1.2719          | 0.4444   |
| 1.3432        | 23.0  | 138  | 1.2696          | 0.4444   |
| 1.3309        | 24.0  | 144  | 1.2677          | 0.4444   |
| 1.3166        | 25.0  | 150  | 1.2667          | 0.4444   |
| 1.3166        | 26.0  | 156  | 1.2651          | 0.4667   |
| 1.3168        | 27.0  | 162  | 1.2639          | 0.4667   |
| 1.3168        | 28.0  | 168  | 1.2624          | 0.4667   |
| 1.3102        | 29.0  | 174  | 1.2615          | 0.4667   |
| 1.3034        | 30.0  | 180  | 1.2602          | 0.4667   |
| 1.3034        | 31.0  | 186  | 1.2590          | 0.4667   |
| 1.3106        | 32.0  | 192  | 1.2580          | 0.4667   |
| 1.3106        | 33.0  | 198  | 1.2570          | 0.4667   |
| 1.2903        | 34.0  | 204  | 1.2562          | 0.4667   |
| 1.2915        | 35.0  | 210  | 1.2554          | 0.4667   |
| 1.2915        | 36.0  | 216  | 1.2549          | 0.4667   |
| 1.2913        | 37.0  | 222  | 1.2546          | 0.4667   |
| 1.2913        | 38.0  | 228  | 1.2542          | 0.4667   |
| 1.2715        | 39.0  | 234  | 1.2539          | 0.4667   |
| 1.2929        | 40.0  | 240  | 1.2538          | 0.4667   |
| 1.2929        | 41.0  | 246  | 1.2537          | 0.4667   |
| 1.2815        | 42.0  | 252  | 1.2536          | 0.4667   |
| 1.2815        | 43.0  | 258  | 1.2536          | 0.4667   |
| 1.2834        | 44.0  | 264  | 1.2536          | 0.4667   |
| 1.2687        | 45.0  | 270  | 1.2536          | 0.4667   |
| 1.2687        | 46.0  | 276  | 1.2536          | 0.4667   |
| 1.2845        | 47.0  | 282  | 1.2536          | 0.4667   |
| 1.2845        | 48.0  | 288  | 1.2536          | 0.4667   |
| 1.2639        | 49.0  | 294  | 1.2536          | 0.4667   |
| 1.2911        | 50.0  | 300  | 1.2536          | 0.4667   |


### Framework versions

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