---
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_fold3
  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: 0.23255813953488372
---

<!-- 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_fold3

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: 1.5102
- Accuracy: 0.2326

## 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    | 1.5815          | 0.2558   |
| 1.5795        | 2.0   | 12   | 1.5768          | 0.2558   |
| 1.5795        | 3.0   | 18   | 1.5725          | 0.2558   |
| 1.5843        | 4.0   | 24   | 1.5685          | 0.2558   |
| 1.5064        | 5.0   | 30   | 1.5650          | 0.2558   |
| 1.5064        | 6.0   | 36   | 1.5613          | 0.2558   |
| 1.5264        | 7.0   | 42   | 1.5577          | 0.2558   |
| 1.5264        | 8.0   | 48   | 1.5544          | 0.2558   |
| 1.5341        | 9.0   | 54   | 1.5511          | 0.2558   |
| 1.5468        | 10.0  | 60   | 1.5482          | 0.2558   |
| 1.5468        | 11.0  | 66   | 1.5458          | 0.2558   |
| 1.5265        | 12.0  | 72   | 1.5432          | 0.2558   |
| 1.5265        | 13.0  | 78   | 1.5409          | 0.2558   |
| 1.4949        | 14.0  | 84   | 1.5386          | 0.2558   |
| 1.5252        | 15.0  | 90   | 1.5362          | 0.2558   |
| 1.5252        | 16.0  | 96   | 1.5341          | 0.2558   |
| 1.5295        | 17.0  | 102  | 1.5321          | 0.2558   |
| 1.5295        | 18.0  | 108  | 1.5302          | 0.2558   |
| 1.4916        | 19.0  | 114  | 1.5284          | 0.2558   |
| 1.4984        | 20.0  | 120  | 1.5267          | 0.2326   |
| 1.4984        | 21.0  | 126  | 1.5250          | 0.2326   |
| 1.5211        | 22.0  | 132  | 1.5235          | 0.2326   |
| 1.5211        | 23.0  | 138  | 1.5222          | 0.2326   |
| 1.506         | 24.0  | 144  | 1.5209          | 0.2326   |
| 1.483         | 25.0  | 150  | 1.5197          | 0.2326   |
| 1.483         | 26.0  | 156  | 1.5185          | 0.2326   |
| 1.5184        | 27.0  | 162  | 1.5173          | 0.2326   |
| 1.5184        | 28.0  | 168  | 1.5163          | 0.2326   |
| 1.536         | 29.0  | 174  | 1.5154          | 0.2326   |
| 1.4949        | 30.0  | 180  | 1.5146          | 0.2326   |
| 1.4949        | 31.0  | 186  | 1.5138          | 0.2326   |
| 1.5188        | 32.0  | 192  | 1.5132          | 0.2326   |
| 1.5188        | 33.0  | 198  | 1.5126          | 0.2326   |
| 1.4387        | 34.0  | 204  | 1.5120          | 0.2326   |
| 1.4953        | 35.0  | 210  | 1.5116          | 0.2326   |
| 1.4953        | 36.0  | 216  | 1.5112          | 0.2326   |
| 1.4703        | 37.0  | 222  | 1.5108          | 0.2326   |
| 1.4703        | 38.0  | 228  | 1.5106          | 0.2326   |
| 1.5017        | 39.0  | 234  | 1.5104          | 0.2326   |
| 1.4757        | 40.0  | 240  | 1.5103          | 0.2326   |
| 1.4757        | 41.0  | 246  | 1.5102          | 0.2326   |
| 1.4714        | 42.0  | 252  | 1.5102          | 0.2326   |
| 1.4714        | 43.0  | 258  | 1.5102          | 0.2326   |
| 1.4776        | 44.0  | 264  | 1.5102          | 0.2326   |
| 1.4921        | 45.0  | 270  | 1.5102          | 0.2326   |
| 1.4921        | 46.0  | 276  | 1.5102          | 0.2326   |
| 1.4896        | 47.0  | 282  | 1.5102          | 0.2326   |
| 1.4896        | 48.0  | 288  | 1.5102          | 0.2326   |
| 1.4789        | 49.0  | 294  | 1.5102          | 0.2326   |
| 1.4671        | 50.0  | 300  | 1.5102          | 0.2326   |


### Framework versions

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