---
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_001_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: 0.5348837209302325
---

<!-- 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_001_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: 1.8097
- Accuracy: 0.5349

## 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    | 1.4381          | 0.2326   |
| 2.0527        | 2.0   | 12   | 1.4022          | 0.2558   |
| 2.0527        | 3.0   | 18   | 1.3682          | 0.3256   |
| 1.3782        | 4.0   | 24   | 1.3387          | 0.3953   |
| 1.2679        | 5.0   | 30   | 1.3721          | 0.3256   |
| 1.2679        | 6.0   | 36   | 1.7451          | 0.3488   |
| 1.2756        | 7.0   | 42   | 1.3183          | 0.3953   |
| 1.2756        | 8.0   | 48   | 1.4225          | 0.3023   |
| 1.173         | 9.0   | 54   | 1.4215          | 0.3953   |
| 1.1959        | 10.0  | 60   | 1.4072          | 0.3721   |
| 1.1959        | 11.0  | 66   | 1.4852          | 0.4186   |
| 1.1344        | 12.0  | 72   | 1.4523          | 0.2791   |
| 1.1344        | 13.0  | 78   | 1.4043          | 0.4651   |
| 1.0854        | 14.0  | 84   | 1.3638          | 0.3953   |
| 1.1124        | 15.0  | 90   | 1.4323          | 0.3953   |
| 1.1124        | 16.0  | 96   | 1.4664          | 0.4884   |
| 1.0108        | 17.0  | 102  | 1.5473          | 0.3721   |
| 1.0108        | 18.0  | 108  | 1.2300          | 0.4651   |
| 0.9443        | 19.0  | 114  | 1.2523          | 0.4419   |
| 0.9125        | 20.0  | 120  | 1.4134          | 0.3721   |
| 0.9125        | 21.0  | 126  | 1.1280          | 0.4884   |
| 0.8328        | 22.0  | 132  | 1.1054          | 0.4884   |
| 0.8328        | 23.0  | 138  | 1.6081          | 0.4419   |
| 0.7565        | 24.0  | 144  | 1.0331          | 0.5349   |
| 0.7135        | 25.0  | 150  | 1.6384          | 0.5116   |
| 0.7135        | 26.0  | 156  | 1.9524          | 0.4651   |
| 0.7048        | 27.0  | 162  | 1.1399          | 0.5349   |
| 0.7048        | 28.0  | 168  | 1.0504          | 0.5581   |
| 0.7074        | 29.0  | 174  | 1.0452          | 0.5581   |
| 0.7008        | 30.0  | 180  | 1.4757          | 0.5581   |
| 0.7008        | 31.0  | 186  | 1.0663          | 0.4419   |
| 0.5976        | 32.0  | 192  | 1.0991          | 0.5349   |
| 0.5976        | 33.0  | 198  | 1.5330          | 0.5814   |
| 0.5565        | 34.0  | 204  | 1.1511          | 0.5349   |
| 0.458         | 35.0  | 210  | 1.5836          | 0.5349   |
| 0.458         | 36.0  | 216  | 1.4225          | 0.5581   |
| 0.5542        | 37.0  | 222  | 1.4182          | 0.6047   |
| 0.5542        | 38.0  | 228  | 1.3407          | 0.5581   |
| 0.3706        | 39.0  | 234  | 1.4368          | 0.5581   |
| 0.3087        | 40.0  | 240  | 1.6899          | 0.5814   |
| 0.3087        | 41.0  | 246  | 1.8110          | 0.5116   |
| 0.3001        | 42.0  | 252  | 1.8097          | 0.5349   |
| 0.3001        | 43.0  | 258  | 1.8097          | 0.5349   |
| 0.3061        | 44.0  | 264  | 1.8097          | 0.5349   |
| 0.2986        | 45.0  | 270  | 1.8097          | 0.5349   |
| 0.2986        | 46.0  | 276  | 1.8097          | 0.5349   |
| 0.2791        | 47.0  | 282  | 1.8097          | 0.5349   |
| 0.2791        | 48.0  | 288  | 1.8097          | 0.5349   |
| 0.2908        | 49.0  | 294  | 1.8097          | 0.5349   |
| 0.2986        | 50.0  | 300  | 1.8097          | 0.5349   |


### Framework versions

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