---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_base_adamax_00001_fold5
  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: 0.7073170731707317
---

<!-- 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_base_adamax_00001_fold5

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co./facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6418
- Accuracy: 0.7073

## 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: 1e-05
- 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    | 1.3016          | 0.3415   |
| 1.352         | 2.0   | 12   | 1.2693          | 0.4878   |
| 1.352         | 3.0   | 18   | 1.2337          | 0.4878   |
| 1.192         | 4.0   | 24   | 1.1939          | 0.5122   |
| 1.066         | 5.0   | 30   | 1.1544          | 0.5854   |
| 1.066         | 6.0   | 36   | 1.1118          | 0.5854   |
| 0.8995        | 7.0   | 42   | 1.0631          | 0.6098   |
| 0.8995        | 8.0   | 48   | 1.0130          | 0.5854   |
| 0.7427        | 9.0   | 54   | 0.9666          | 0.6341   |
| 0.6143        | 10.0  | 60   | 0.9418          | 0.6098   |
| 0.6143        | 11.0  | 66   | 0.9096          | 0.6341   |
| 0.4971        | 12.0  | 72   | 0.8791          | 0.6341   |
| 0.4971        | 13.0  | 78   | 0.8576          | 0.6341   |
| 0.3974        | 14.0  | 84   | 0.8299          | 0.6341   |
| 0.3312        | 15.0  | 90   | 0.8125          | 0.6585   |
| 0.3312        | 16.0  | 96   | 0.7924          | 0.6585   |
| 0.2583        | 17.0  | 102  | 0.7878          | 0.6341   |
| 0.2583        | 18.0  | 108  | 0.7665          | 0.6341   |
| 0.2053        | 19.0  | 114  | 0.7402          | 0.6585   |
| 0.1711        | 20.0  | 120  | 0.7303          | 0.6585   |
| 0.1711        | 21.0  | 126  | 0.7219          | 0.6585   |
| 0.1383        | 22.0  | 132  | 0.7157          | 0.6341   |
| 0.1383        | 23.0  | 138  | 0.6921          | 0.6585   |
| 0.1073        | 24.0  | 144  | 0.6843          | 0.6585   |
| 0.0942        | 25.0  | 150  | 0.6833          | 0.6585   |
| 0.0942        | 26.0  | 156  | 0.6687          | 0.6585   |
| 0.0772        | 27.0  | 162  | 0.6726          | 0.7073   |
| 0.0772        | 28.0  | 168  | 0.6619          | 0.6585   |
| 0.0641        | 29.0  | 174  | 0.6481          | 0.6585   |
| 0.0563        | 30.0  | 180  | 0.6452          | 0.7073   |
| 0.0563        | 31.0  | 186  | 0.6508          | 0.7073   |
| 0.0487        | 32.0  | 192  | 0.6523          | 0.7073   |
| 0.0487        | 33.0  | 198  | 0.6468          | 0.7073   |
| 0.0422        | 34.0  | 204  | 0.6452          | 0.7073   |
| 0.0402        | 35.0  | 210  | 0.6443          | 0.7073   |
| 0.0402        | 36.0  | 216  | 0.6441          | 0.7073   |
| 0.0375        | 37.0  | 222  | 0.6438          | 0.7073   |
| 0.0375        | 38.0  | 228  | 0.6434          | 0.7073   |
| 0.0345        | 39.0  | 234  | 0.6428          | 0.7073   |
| 0.0342        | 40.0  | 240  | 0.6422          | 0.7073   |
| 0.0342        | 41.0  | 246  | 0.6417          | 0.7073   |
| 0.0339        | 42.0  | 252  | 0.6418          | 0.7073   |
| 0.0339        | 43.0  | 258  | 0.6418          | 0.7073   |
| 0.0327        | 44.0  | 264  | 0.6418          | 0.7073   |
| 0.0338        | 45.0  | 270  | 0.6418          | 0.7073   |
| 0.0338        | 46.0  | 276  | 0.6418          | 0.7073   |
| 0.033         | 47.0  | 282  | 0.6418          | 0.7073   |
| 0.033         | 48.0  | 288  | 0.6418          | 0.7073   |
| 0.0336        | 49.0  | 294  | 0.6418          | 0.7073   |
| 0.0342        | 50.0  | 300  | 0.6418          | 0.7073   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0