---
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_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: 0.26666666666666666
---

<!-- 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_sgd_0001_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: 1.4763
- Accuracy: 0.2667

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.5508          | 0.2667   |
| 1.5993        | 2.0   | 12   | 1.5460          | 0.2667   |
| 1.5993        | 3.0   | 18   | 1.5415          | 0.2667   |
| 1.5379        | 4.0   | 24   | 1.5376          | 0.2667   |
| 1.5842        | 5.0   | 30   | 1.5337          | 0.2667   |
| 1.5842        | 6.0   | 36   | 1.5302          | 0.2667   |
| 1.5559        | 7.0   | 42   | 1.5267          | 0.2667   |
| 1.5559        | 8.0   | 48   | 1.5233          | 0.2667   |
| 1.5583        | 9.0   | 54   | 1.5200          | 0.2667   |
| 1.5216        | 10.0  | 60   | 1.5170          | 0.2667   |
| 1.5216        | 11.0  | 66   | 1.5141          | 0.2667   |
| 1.5475        | 12.0  | 72   | 1.5116          | 0.2667   |
| 1.5475        | 13.0  | 78   | 1.5088          | 0.2667   |
| 1.5228        | 14.0  | 84   | 1.5063          | 0.2667   |
| 1.5337        | 15.0  | 90   | 1.5038          | 0.2667   |
| 1.5337        | 16.0  | 96   | 1.5015          | 0.2667   |
| 1.5424        | 17.0  | 102  | 1.4994          | 0.2667   |
| 1.5424        | 18.0  | 108  | 1.4973          | 0.2667   |
| 1.5261        | 19.0  | 114  | 1.4953          | 0.2667   |
| 1.5374        | 20.0  | 120  | 1.4936          | 0.2667   |
| 1.5374        | 21.0  | 126  | 1.4921          | 0.2667   |
| 1.5211        | 22.0  | 132  | 1.4905          | 0.2667   |
| 1.5211        | 23.0  | 138  | 1.4888          | 0.2667   |
| 1.5308        | 24.0  | 144  | 1.4875          | 0.2667   |
| 1.501         | 25.0  | 150  | 1.4863          | 0.2667   |
| 1.501         | 26.0  | 156  | 1.4851          | 0.2667   |
| 1.4969        | 27.0  | 162  | 1.4841          | 0.2667   |
| 1.4969        | 28.0  | 168  | 1.4832          | 0.2667   |
| 1.4796        | 29.0  | 174  | 1.4822          | 0.2667   |
| 1.5135        | 30.0  | 180  | 1.4813          | 0.2667   |
| 1.5135        | 31.0  | 186  | 1.4804          | 0.2667   |
| 1.4924        | 32.0  | 192  | 1.4797          | 0.2667   |
| 1.4924        | 33.0  | 198  | 1.4791          | 0.2667   |
| 1.4838        | 34.0  | 204  | 1.4785          | 0.2667   |
| 1.4833        | 35.0  | 210  | 1.4779          | 0.2667   |
| 1.4833        | 36.0  | 216  | 1.4775          | 0.2667   |
| 1.4826        | 37.0  | 222  | 1.4771          | 0.2667   |
| 1.4826        | 38.0  | 228  | 1.4768          | 0.2667   |
| 1.5058        | 39.0  | 234  | 1.4766          | 0.2667   |
| 1.4814        | 40.0  | 240  | 1.4764          | 0.2667   |
| 1.4814        | 41.0  | 246  | 1.4764          | 0.2667   |
| 1.4809        | 42.0  | 252  | 1.4763          | 0.2667   |
| 1.4809        | 43.0  | 258  | 1.4763          | 0.2667   |
| 1.5264        | 44.0  | 264  | 1.4763          | 0.2667   |
| 1.4935        | 45.0  | 270  | 1.4763          | 0.2667   |
| 1.4935        | 46.0  | 276  | 1.4763          | 0.2667   |
| 1.4909        | 47.0  | 282  | 1.4763          | 0.2667   |
| 1.4909        | 48.0  | 288  | 1.4763          | 0.2667   |
| 1.4851        | 49.0  | 294  | 1.4763          | 0.2667   |
| 1.5045        | 50.0  | 300  | 1.4763          | 0.2667   |


### Framework versions

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