---
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_adamax_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: 0.7333333333333333
---

<!-- 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_adamax_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: 1.6564
- Accuracy: 0.7333

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6698        | 1.0   | 27   | 0.9988          | 0.6889   |
| 0.1411        | 2.0   | 54   | 1.0160          | 0.8      |
| 0.0271        | 3.0   | 81   | 1.0366          | 0.8222   |
| 0.0097        | 4.0   | 108  | 1.1864          | 0.7778   |
| 0.0327        | 5.0   | 135  | 1.1344          | 0.7333   |
| 0.001         | 6.0   | 162  | 1.5092          | 0.7556   |
| 0.0005        | 7.0   | 189  | 1.7651          | 0.7111   |
| 0.0003        | 8.0   | 216  | 1.6487          | 0.7111   |
| 0.0002        | 9.0   | 243  | 1.5798          | 0.7333   |
| 0.0001        | 10.0  | 270  | 1.5740          | 0.7333   |
| 0.0001        | 11.0  | 297  | 1.5833          | 0.7333   |
| 0.0001        | 12.0  | 324  | 1.5855          | 0.7333   |
| 0.0001        | 13.0  | 351  | 1.5914          | 0.7333   |
| 0.0001        | 14.0  | 378  | 1.5933          | 0.7333   |
| 0.0001        | 15.0  | 405  | 1.5965          | 0.7333   |
| 0.0001        | 16.0  | 432  | 1.6012          | 0.7333   |
| 0.0001        | 17.0  | 459  | 1.6053          | 0.7333   |
| 0.0001        | 18.0  | 486  | 1.6065          | 0.7333   |
| 0.0001        | 19.0  | 513  | 1.6095          | 0.7333   |
| 0.0001        | 20.0  | 540  | 1.6122          | 0.7333   |
| 0.0001        | 21.0  | 567  | 1.6156          | 0.7333   |
| 0.0001        | 22.0  | 594  | 1.6199          | 0.7333   |
| 0.0001        | 23.0  | 621  | 1.6206          | 0.7333   |
| 0.0001        | 24.0  | 648  | 1.6254          | 0.7333   |
| 0.0001        | 25.0  | 675  | 1.6261          | 0.7333   |
| 0.0001        | 26.0  | 702  | 1.6276          | 0.7333   |
| 0.0001        | 27.0  | 729  | 1.6298          | 0.7333   |
| 0.0001        | 28.0  | 756  | 1.6336          | 0.7333   |
| 0.0001        | 29.0  | 783  | 1.6342          | 0.7333   |
| 0.0001        | 30.0  | 810  | 1.6366          | 0.7333   |
| 0.0001        | 31.0  | 837  | 1.6386          | 0.7333   |
| 0.0001        | 32.0  | 864  | 1.6401          | 0.7333   |
| 0.0001        | 33.0  | 891  | 1.6423          | 0.7333   |
| 0.0001        | 34.0  | 918  | 1.6444          | 0.7333   |
| 0.0           | 35.0  | 945  | 1.6463          | 0.7333   |
| 0.0           | 36.0  | 972  | 1.6470          | 0.7333   |
| 0.0           | 37.0  | 999  | 1.6481          | 0.7333   |
| 0.0           | 38.0  | 1026 | 1.6495          | 0.7333   |
| 0.0           | 39.0  | 1053 | 1.6509          | 0.7333   |
| 0.0           | 40.0  | 1080 | 1.6519          | 0.7333   |
| 0.0           | 41.0  | 1107 | 1.6529          | 0.7333   |
| 0.0           | 42.0  | 1134 | 1.6540          | 0.7333   |
| 0.0           | 43.0  | 1161 | 1.6547          | 0.7333   |
| 0.0           | 44.0  | 1188 | 1.6550          | 0.7333   |
| 0.0           | 45.0  | 1215 | 1.6554          | 0.7333   |
| 0.0           | 46.0  | 1242 | 1.6560          | 0.7333   |
| 0.0           | 47.0  | 1269 | 1.6562          | 0.7333   |
| 0.0           | 48.0  | 1296 | 1.6564          | 0.7333   |
| 0.0           | 49.0  | 1323 | 1.6564          | 0.7333   |
| 0.0           | 50.0  | 1350 | 1.6564          | 0.7333   |


### Framework versions

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