---
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_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: 0.3333333333333333
---

<!-- 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_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: 1.3896
- Accuracy: 0.3333

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5183        | 1.0   | 27   | 1.5038          | 0.1778   |
| 1.502         | 2.0   | 54   | 1.4946          | 0.2      |
| 1.5109        | 3.0   | 81   | 1.4859          | 0.2222   |
| 1.5446        | 4.0   | 108  | 1.4781          | 0.2444   |
| 1.4687        | 5.0   | 135  | 1.4710          | 0.2444   |
| 1.4554        | 6.0   | 162  | 1.4641          | 0.2889   |
| 1.4113        | 7.0   | 189  | 1.4582          | 0.2889   |
| 1.4434        | 8.0   | 216  | 1.4525          | 0.2667   |
| 1.4243        | 9.0   | 243  | 1.4473          | 0.2667   |
| 1.4268        | 10.0  | 270  | 1.4425          | 0.2889   |
| 1.386         | 11.0  | 297  | 1.4382          | 0.2889   |
| 1.4235        | 12.0  | 324  | 1.4341          | 0.2667   |
| 1.4228        | 13.0  | 351  | 1.4304          | 0.2667   |
| 1.4091        | 14.0  | 378  | 1.4269          | 0.2889   |
| 1.4135        | 15.0  | 405  | 1.4239          | 0.2667   |
| 1.4228        | 16.0  | 432  | 1.4210          | 0.2889   |
| 1.4188        | 17.0  | 459  | 1.4184          | 0.2889   |
| 1.3824        | 18.0  | 486  | 1.4159          | 0.3333   |
| 1.3861        | 19.0  | 513  | 1.4136          | 0.3111   |
| 1.393         | 20.0  | 540  | 1.4115          | 0.3111   |
| 1.4051        | 21.0  | 567  | 1.4096          | 0.3111   |
| 1.373         | 22.0  | 594  | 1.4077          | 0.3333   |
| 1.3737        | 23.0  | 621  | 1.4060          | 0.3333   |
| 1.3668        | 24.0  | 648  | 1.4044          | 0.3556   |
| 1.362         | 25.0  | 675  | 1.4030          | 0.3556   |
| 1.3931        | 26.0  | 702  | 1.4016          | 0.3556   |
| 1.3504        | 27.0  | 729  | 1.4003          | 0.3556   |
| 1.3706        | 28.0  | 756  | 1.3992          | 0.3556   |
| 1.359         | 29.0  | 783  | 1.3981          | 0.3556   |
| 1.3774        | 30.0  | 810  | 1.3972          | 0.3556   |
| 1.3678        | 31.0  | 837  | 1.3963          | 0.3556   |
| 1.3418        | 32.0  | 864  | 1.3955          | 0.3556   |
| 1.3702        | 33.0  | 891  | 1.3947          | 0.3556   |
| 1.3589        | 34.0  | 918  | 1.3940          | 0.3556   |
| 1.3212        | 35.0  | 945  | 1.3933          | 0.3333   |
| 1.3648        | 36.0  | 972  | 1.3928          | 0.3333   |
| 1.3509        | 37.0  | 999  | 1.3922          | 0.3333   |
| 1.3506        | 38.0  | 1026 | 1.3917          | 0.3333   |
| 1.3673        | 39.0  | 1053 | 1.3913          | 0.3333   |
| 1.3657        | 40.0  | 1080 | 1.3910          | 0.3333   |
| 1.3651        | 41.0  | 1107 | 1.3906          | 0.3333   |
| 1.3688        | 42.0  | 1134 | 1.3904          | 0.3333   |
| 1.3871        | 43.0  | 1161 | 1.3901          | 0.3333   |
| 1.3307        | 44.0  | 1188 | 1.3899          | 0.3333   |
| 1.3505        | 45.0  | 1215 | 1.3898          | 0.3333   |
| 1.3367        | 46.0  | 1242 | 1.3897          | 0.3333   |
| 1.3605        | 47.0  | 1269 | 1.3896          | 0.3333   |
| 1.3556        | 48.0  | 1296 | 1.3896          | 0.3333   |
| 1.3876        | 49.0  | 1323 | 1.3896          | 0.3333   |
| 1.3357        | 50.0  | 1350 | 1.3896          | 0.3333   |


### Framework versions

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