---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_small_sgd_0001_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: 0.3111111111111111
---

<!-- 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_5x_deit_small_sgd_0001_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: 1.3695
- Accuracy: 0.3111

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5195        | 1.0   | 27   | 1.4999          | 0.2889   |
| 1.4914        | 2.0   | 54   | 1.4892          | 0.2889   |
| 1.5108        | 3.0   | 81   | 1.4789          | 0.2889   |
| 1.5345        | 4.0   | 108  | 1.4698          | 0.2667   |
| 1.4684        | 5.0   | 135  | 1.4617          | 0.2667   |
| 1.4525        | 6.0   | 162  | 1.4534          | 0.2667   |
| 1.4298        | 7.0   | 189  | 1.4465          | 0.2667   |
| 1.4569        | 8.0   | 216  | 1.4397          | 0.2444   |
| 1.4283        | 9.0   | 243  | 1.4337          | 0.2444   |
| 1.4203        | 10.0  | 270  | 1.4280          | 0.2444   |
| 1.3871        | 11.0  | 297  | 1.4228          | 0.2444   |
| 1.4156        | 12.0  | 324  | 1.4180          | 0.2444   |
| 1.4346        | 13.0  | 351  | 1.4134          | 0.2444   |
| 1.4076        | 14.0  | 378  | 1.4093          | 0.2444   |
| 1.425         | 15.0  | 405  | 1.4059          | 0.2444   |
| 1.4406        | 16.0  | 432  | 1.4025          | 0.2444   |
| 1.4069        | 17.0  | 459  | 1.3996          | 0.2444   |
| 1.3779        | 18.0  | 486  | 1.3968          | 0.2444   |
| 1.3991        | 19.0  | 513  | 1.3941          | 0.2667   |
| 1.3962        | 20.0  | 540  | 1.3918          | 0.2667   |
| 1.3954        | 21.0  | 567  | 1.3897          | 0.2889   |
| 1.3886        | 22.0  | 594  | 1.3877          | 0.2889   |
| 1.3775        | 23.0  | 621  | 1.3858          | 0.2889   |
| 1.3714        | 24.0  | 648  | 1.3842          | 0.2889   |
| 1.4056        | 25.0  | 675  | 1.3826          | 0.2889   |
| 1.4026        | 26.0  | 702  | 1.3812          | 0.2889   |
| 1.359         | 27.0  | 729  | 1.3799          | 0.2889   |
| 1.3709        | 28.0  | 756  | 1.3787          | 0.2889   |
| 1.3667        | 29.0  | 783  | 1.3776          | 0.2889   |
| 1.3672        | 30.0  | 810  | 1.3766          | 0.2889   |
| 1.3762        | 31.0  | 837  | 1.3757          | 0.2889   |
| 1.3384        | 32.0  | 864  | 1.3749          | 0.2889   |
| 1.3698        | 33.0  | 891  | 1.3742          | 0.2889   |
| 1.3636        | 34.0  | 918  | 1.3735          | 0.3111   |
| 1.3439        | 35.0  | 945  | 1.3729          | 0.3111   |
| 1.3571        | 36.0  | 972  | 1.3723          | 0.3111   |
| 1.3688        | 37.0  | 999  | 1.3718          | 0.3111   |
| 1.3527        | 38.0  | 1026 | 1.3714          | 0.3111   |
| 1.3641        | 39.0  | 1053 | 1.3710          | 0.3111   |
| 1.3538        | 40.0  | 1080 | 1.3707          | 0.3111   |
| 1.3693        | 41.0  | 1107 | 1.3704          | 0.3111   |
| 1.3789        | 42.0  | 1134 | 1.3701          | 0.3111   |
| 1.3917        | 43.0  | 1161 | 1.3699          | 0.3111   |
| 1.3524        | 44.0  | 1188 | 1.3698          | 0.3111   |
| 1.367         | 45.0  | 1215 | 1.3696          | 0.3111   |
| 1.3553        | 46.0  | 1242 | 1.3696          | 0.3111   |
| 1.3523        | 47.0  | 1269 | 1.3695          | 0.3111   |
| 1.3646        | 48.0  | 1296 | 1.3695          | 0.3111   |
| 1.3891        | 49.0  | 1323 | 1.3695          | 0.3111   |
| 1.3396        | 50.0  | 1350 | 1.3695          | 0.3111   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0