---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_sgd_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: 0.26666666666666666
---

<!-- 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_5x_beit_base_sgd_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: 1.5367
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5006        | 1.0   | 27   | 1.5552          | 0.2667   |
| 1.5759        | 2.0   | 54   | 1.5543          | 0.2667   |
| 1.5707        | 3.0   | 81   | 1.5535          | 0.2667   |
| 1.578         | 4.0   | 108  | 1.5527          | 0.2667   |
| 1.5119        | 5.0   | 135  | 1.5520          | 0.2667   |
| 1.5352        | 6.0   | 162  | 1.5512          | 0.2667   |
| 1.5348        | 7.0   | 189  | 1.5504          | 0.2667   |
| 1.5693        | 8.0   | 216  | 1.5497          | 0.2667   |
| 1.5386        | 9.0   | 243  | 1.5490          | 0.2667   |
| 1.5189        | 10.0  | 270  | 1.5483          | 0.2667   |
| 1.5597        | 11.0  | 297  | 1.5477          | 0.2667   |
| 1.5706        | 12.0  | 324  | 1.5471          | 0.2667   |
| 1.5157        | 13.0  | 351  | 1.5465          | 0.2667   |
| 1.5457        | 14.0  | 378  | 1.5458          | 0.2667   |
| 1.5087        | 15.0  | 405  | 1.5453          | 0.2667   |
| 1.5323        | 16.0  | 432  | 1.5447          | 0.2667   |
| 1.5363        | 17.0  | 459  | 1.5442          | 0.2667   |
| 1.5615        | 18.0  | 486  | 1.5437          | 0.2667   |
| 1.5236        | 19.0  | 513  | 1.5433          | 0.2667   |
| 1.566         | 20.0  | 540  | 1.5428          | 0.2667   |
| 1.5446        | 21.0  | 567  | 1.5424          | 0.2667   |
| 1.5289        | 22.0  | 594  | 1.5419          | 0.2667   |
| 1.4823        | 23.0  | 621  | 1.5415          | 0.2667   |
| 1.5025        | 24.0  | 648  | 1.5411          | 0.2667   |
| 1.5362        | 25.0  | 675  | 1.5407          | 0.2667   |
| 1.5593        | 26.0  | 702  | 1.5404          | 0.2667   |
| 1.5515        | 27.0  | 729  | 1.5401          | 0.2667   |
| 1.5275        | 28.0  | 756  | 1.5397          | 0.2667   |
| 1.5171        | 29.0  | 783  | 1.5394          | 0.2667   |
| 1.5816        | 30.0  | 810  | 1.5391          | 0.2667   |
| 1.5294        | 31.0  | 837  | 1.5389          | 0.2667   |
| 1.5276        | 32.0  | 864  | 1.5386          | 0.2667   |
| 1.5584        | 33.0  | 891  | 1.5384          | 0.2667   |
| 1.5549        | 34.0  | 918  | 1.5382          | 0.2667   |
| 1.4864        | 35.0  | 945  | 1.5380          | 0.2667   |
| 1.4851        | 36.0  | 972  | 1.5378          | 0.2667   |
| 1.4835        | 37.0  | 999  | 1.5376          | 0.2667   |
| 1.5708        | 38.0  | 1026 | 1.5374          | 0.2667   |
| 1.5448        | 39.0  | 1053 | 1.5373          | 0.2667   |
| 1.4945        | 40.0  | 1080 | 1.5372          | 0.2667   |
| 1.486         | 41.0  | 1107 | 1.5371          | 0.2667   |
| 1.5082        | 42.0  | 1134 | 1.5370          | 0.2667   |
| 1.5323        | 43.0  | 1161 | 1.5369          | 0.2667   |
| 1.4965        | 44.0  | 1188 | 1.5368          | 0.2667   |
| 1.5407        | 45.0  | 1215 | 1.5368          | 0.2667   |
| 1.5084        | 46.0  | 1242 | 1.5368          | 0.2667   |
| 1.5191        | 47.0  | 1269 | 1.5367          | 0.2667   |
| 1.5617        | 48.0  | 1296 | 1.5367          | 0.2667   |
| 1.4992        | 49.0  | 1323 | 1.5367          | 0.2667   |
| 1.4782        | 50.0  | 1350 | 1.5367          | 0.2667   |


### Framework versions

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