---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_sgd_0001_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: 0.5111111111111111
---

<!-- 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_40x_deit_small_sgd_0001_fold2

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: 1.2548
- Accuracy: 0.5111

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.7252        | 1.0   | 215   | 1.5329          | 0.2667   |
| 1.5501        | 2.0   | 430   | 1.4609          | 0.3111   |
| 1.4663        | 3.0   | 645   | 1.4250          | 0.3111   |
| 1.4117        | 4.0   | 860   | 1.4032          | 0.2889   |
| 1.3533        | 5.0   | 1075  | 1.3870          | 0.2667   |
| 1.3221        | 6.0   | 1290  | 1.3733          | 0.2889   |
| 1.3111        | 7.0   | 1505  | 1.3613          | 0.3111   |
| 1.2698        | 8.0   | 1720  | 1.3509          | 0.3111   |
| 1.2425        | 9.0   | 1935  | 1.3418          | 0.3111   |
| 1.2243        | 10.0  | 2150  | 1.3338          | 0.3778   |
| 1.2016        | 11.0  | 2365  | 1.3268          | 0.3778   |
| 1.1128        | 12.0  | 2580  | 1.3203          | 0.3556   |
| 1.174         | 13.0  | 2795  | 1.3136          | 0.3556   |
| 1.1731        | 14.0  | 3010  | 1.3081          | 0.4      |
| 1.141         | 15.0  | 3225  | 1.3031          | 0.4      |
| 1.1163        | 16.0  | 3440  | 1.2979          | 0.4      |
| 1.1128        | 17.0  | 3655  | 1.2946          | 0.4222   |
| 1.0806        | 18.0  | 3870  | 1.2916          | 0.4222   |
| 1.0332        | 19.0  | 4085  | 1.2893          | 0.3778   |
| 1.0358        | 20.0  | 4300  | 1.2875          | 0.4      |
| 1.0352        | 21.0  | 4515  | 1.2855          | 0.4      |
| 1.0257        | 22.0  | 4730  | 1.2838          | 0.4      |
| 1.0362        | 23.0  | 4945  | 1.2822          | 0.4      |
| 1.0137        | 24.0  | 5160  | 1.2805          | 0.4      |
| 1.0067        | 25.0  | 5375  | 1.2787          | 0.4222   |
| 0.9834        | 26.0  | 5590  | 1.2771          | 0.4667   |
| 0.9889        | 27.0  | 5805  | 1.2753          | 0.4667   |
| 0.9291        | 28.0  | 6020  | 1.2744          | 0.4667   |
| 0.9563        | 29.0  | 6235  | 1.2728          | 0.4667   |
| 0.9949        | 30.0  | 6450  | 1.2710          | 0.4667   |
| 0.9331        | 31.0  | 6665  | 1.2698          | 0.4667   |
| 0.9189        | 32.0  | 6880  | 1.2683          | 0.4889   |
| 0.8977        | 33.0  | 7095  | 1.2667          | 0.4889   |
| 0.9506        | 34.0  | 7310  | 1.2657          | 0.4889   |
| 0.9018        | 35.0  | 7525  | 1.2644          | 0.4889   |
| 0.9085        | 36.0  | 7740  | 1.2632          | 0.4889   |
| 0.9525        | 37.0  | 7955  | 1.2617          | 0.4889   |
| 0.9147        | 38.0  | 8170  | 1.2608          | 0.4889   |
| 0.8837        | 39.0  | 8385  | 1.2597          | 0.5111   |
| 0.9228        | 40.0  | 8600  | 1.2588          | 0.5111   |
| 0.8773        | 41.0  | 8815  | 1.2582          | 0.5111   |
| 0.8964        | 42.0  | 9030  | 1.2574          | 0.5111   |
| 0.8892        | 43.0  | 9245  | 1.2568          | 0.5111   |
| 0.8986        | 44.0  | 9460  | 1.2562          | 0.5111   |
| 0.9114        | 45.0  | 9675  | 1.2557          | 0.5111   |
| 0.8745        | 46.0  | 9890  | 1.2553          | 0.5111   |
| 0.9224        | 47.0  | 10105 | 1.2551          | 0.5111   |
| 0.9229        | 48.0  | 10320 | 1.2549          | 0.5111   |
| 0.9087        | 49.0  | 10535 | 1.2549          | 0.5111   |
| 0.9371        | 50.0  | 10750 | 1.2548          | 0.5111   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2