---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_beit_base_adamax_00001_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: 0.6888888888888889
---

<!-- 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_beit_base_adamax_00001_fold2

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0038
- Accuracy: 0.6889

## 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    | 1.2765          | 0.4      |
| 1.3322        | 2.0   | 12   | 1.2154          | 0.4444   |
| 1.3322        | 3.0   | 18   | 1.1631          | 0.4889   |
| 0.9388        | 4.0   | 24   | 1.0966          | 0.4889   |
| 0.7193        | 5.0   | 30   | 1.0653          | 0.6      |
| 0.7193        | 6.0   | 36   | 1.0660          | 0.5556   |
| 0.5374        | 7.0   | 42   | 1.0203          | 0.5778   |
| 0.5374        | 8.0   | 48   | 1.0147          | 0.6      |
| 0.4187        | 9.0   | 54   | 1.0003          | 0.6222   |
| 0.3224        | 10.0  | 60   | 0.9783          | 0.6      |
| 0.3224        | 11.0  | 66   | 0.9383          | 0.6444   |
| 0.2464        | 12.0  | 72   | 0.9513          | 0.6444   |
| 0.2464        | 13.0  | 78   | 0.9808          | 0.6444   |
| 0.1839        | 14.0  | 84   | 0.9939          | 0.6667   |
| 0.1568        | 15.0  | 90   | 1.0128          | 0.6667   |
| 0.1568        | 16.0  | 96   | 0.9589          | 0.6889   |
| 0.1288        | 17.0  | 102  | 0.9172          | 0.6889   |
| 0.1288        | 18.0  | 108  | 0.9617          | 0.6667   |
| 0.1076        | 19.0  | 114  | 0.9784          | 0.6889   |
| 0.1101        | 20.0  | 120  | 0.9555          | 0.6889   |
| 0.1101        | 21.0  | 126  | 0.9639          | 0.6889   |
| 0.0715        | 22.0  | 132  | 1.0124          | 0.6667   |
| 0.0715        | 23.0  | 138  | 1.0281          | 0.6889   |
| 0.0643        | 24.0  | 144  | 0.9837          | 0.6889   |
| 0.062         | 25.0  | 150  | 0.9706          | 0.6889   |
| 0.062         | 26.0  | 156  | 0.9680          | 0.6889   |
| 0.0557        | 27.0  | 162  | 0.9640          | 0.6889   |
| 0.0557        | 28.0  | 168  | 0.9912          | 0.6889   |
| 0.0524        | 29.0  | 174  | 1.0047          | 0.7111   |
| 0.0432        | 30.0  | 180  | 1.0048          | 0.6889   |
| 0.0432        | 31.0  | 186  | 1.0092          | 0.6889   |
| 0.0454        | 32.0  | 192  | 1.0117          | 0.6889   |
| 0.0454        | 33.0  | 198  | 1.0112          | 0.6889   |
| 0.0405        | 34.0  | 204  | 0.9915          | 0.6889   |
| 0.0406        | 35.0  | 210  | 0.9689          | 0.6889   |
| 0.0406        | 36.0  | 216  | 0.9643          | 0.6889   |
| 0.0354        | 37.0  | 222  | 0.9716          | 0.6889   |
| 0.0354        | 38.0  | 228  | 0.9874          | 0.6889   |
| 0.0426        | 39.0  | 234  | 0.9950          | 0.6889   |
| 0.0369        | 40.0  | 240  | 0.9999          | 0.6889   |
| 0.0369        | 41.0  | 246  | 1.0036          | 0.6889   |
| 0.0338        | 42.0  | 252  | 1.0038          | 0.6889   |
| 0.0338        | 43.0  | 258  | 1.0038          | 0.6889   |
| 0.0349        | 44.0  | 264  | 1.0038          | 0.6889   |
| 0.0361        | 45.0  | 270  | 1.0038          | 0.6889   |
| 0.0361        | 46.0  | 276  | 1.0038          | 0.6889   |
| 0.0398        | 47.0  | 282  | 1.0038          | 0.6889   |
| 0.0398        | 48.0  | 288  | 1.0038          | 0.6889   |
| 0.0375        | 49.0  | 294  | 1.0038          | 0.6889   |
| 0.0265        | 50.0  | 300  | 1.0038          | 0.6889   |


### Framework versions

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