---
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_rms_001_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: 0.5609756097560976
---

<!-- 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_rms_001_fold5

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: 1.0249
- Accuracy: 0.5610

## 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: 0.001
- 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    | 4.0765          | 0.2683   |
| 4.3424        | 2.0   | 12   | 1.4584          | 0.2439   |
| 4.3424        | 3.0   | 18   | 1.4177          | 0.2439   |
| 1.6981        | 4.0   | 24   | 1.4396          | 0.2439   |
| 1.439         | 5.0   | 30   | 1.4302          | 0.2439   |
| 1.439         | 6.0   | 36   | 1.4113          | 0.2683   |
| 1.4514        | 7.0   | 42   | 1.4298          | 0.2439   |
| 1.4514        | 8.0   | 48   | 1.4142          | 0.2683   |
| 1.4037        | 9.0   | 54   | 1.3909          | 0.2683   |
| 1.4226        | 10.0  | 60   | 1.3819          | 0.2683   |
| 1.4226        | 11.0  | 66   | 1.3922          | 0.2683   |
| 1.3954        | 12.0  | 72   | 1.3475          | 0.2195   |
| 1.3954        | 13.0  | 78   | 1.3669          | 0.2439   |
| 1.4193        | 14.0  | 84   | 1.3582          | 0.2683   |
| 1.3817        | 15.0  | 90   | 1.3869          | 0.2439   |
| 1.3817        | 16.0  | 96   | 1.6362          | 0.2439   |
| 1.3794        | 17.0  | 102  | 1.4473          | 0.2439   |
| 1.3794        | 18.0  | 108  | 1.3118          | 0.4146   |
| 1.3773        | 19.0  | 114  | 1.3101          | 0.3415   |
| 1.3081        | 20.0  | 120  | 1.4119          | 0.2439   |
| 1.3081        | 21.0  | 126  | 1.2040          | 0.4634   |
| 1.2767        | 22.0  | 132  | 2.0544          | 0.2439   |
| 1.2767        | 23.0  | 138  | 1.2316          | 0.3415   |
| 1.3145        | 24.0  | 144  | 1.3728          | 0.2683   |
| 1.2519        | 25.0  | 150  | 1.3114          | 0.2927   |
| 1.2519        | 26.0  | 156  | 1.1523          | 0.5122   |
| 1.2177        | 27.0  | 162  | 1.1097          | 0.4634   |
| 1.2177        | 28.0  | 168  | 1.2516          | 0.3902   |
| 1.1299        | 29.0  | 174  | 1.1372          | 0.4390   |
| 1.1588        | 30.0  | 180  | 1.1704          | 0.4146   |
| 1.1588        | 31.0  | 186  | 1.0311          | 0.5610   |
| 1.1686        | 32.0  | 192  | 1.0730          | 0.4634   |
| 1.1686        | 33.0  | 198  | 1.0832          | 0.4634   |
| 1.038         | 34.0  | 204  | 1.1414          | 0.4878   |
| 1.0117        | 35.0  | 210  | 0.9564          | 0.6585   |
| 1.0117        | 36.0  | 216  | 1.1782          | 0.4146   |
| 1.0097        | 37.0  | 222  | 1.0629          | 0.5122   |
| 1.0097        | 38.0  | 228  | 1.0278          | 0.4634   |
| 0.9459        | 39.0  | 234  | 1.0014          | 0.5610   |
| 0.8786        | 40.0  | 240  | 0.9935          | 0.5854   |
| 0.8786        | 41.0  | 246  | 1.0190          | 0.5610   |
| 0.8792        | 42.0  | 252  | 1.0249          | 0.5610   |
| 0.8792        | 43.0  | 258  | 1.0249          | 0.5610   |
| 0.7834        | 44.0  | 264  | 1.0249          | 0.5610   |
| 0.8444        | 45.0  | 270  | 1.0249          | 0.5610   |
| 0.8444        | 46.0  | 276  | 1.0249          | 0.5610   |
| 0.8306        | 47.0  | 282  | 1.0249          | 0.5610   |
| 0.8306        | 48.0  | 288  | 1.0249          | 0.5610   |
| 0.8546        | 49.0  | 294  | 1.0249          | 0.5610   |
| 0.8485        | 50.0  | 300  | 1.0249          | 0.5610   |


### Framework versions

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