---
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_rms_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: 0.8666666666666667
---

<!-- 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_rms_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: 0.8184
- Accuracy: 0.8667

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6865        | 1.0   | 27   | 0.7969          | 0.7556   |
| 0.1615        | 2.0   | 54   | 0.9353          | 0.7778   |
| 0.041         | 3.0   | 81   | 1.0745          | 0.6444   |
| 0.0119        | 4.0   | 108  | 1.0481          | 0.7333   |
| 0.0095        | 5.0   | 135  | 0.6063          | 0.8667   |
| 0.0013        | 6.0   | 162  | 0.6520          | 0.8444   |
| 0.0015        | 7.0   | 189  | 0.7604          | 0.8667   |
| 0.0013        | 8.0   | 216  | 0.7595          | 0.8444   |
| 0.0008        | 9.0   | 243  | 0.8299          | 0.8444   |
| 0.0008        | 10.0  | 270  | 0.6509          | 0.8444   |
| 0.0009        | 11.0  | 297  | 0.7989          | 0.8444   |
| 0.0002        | 12.0  | 324  | 0.8458          | 0.8444   |
| 0.0005        | 13.0  | 351  | 0.6321          | 0.8667   |
| 0.0002        | 14.0  | 378  | 0.6972          | 0.8444   |
| 0.0002        | 15.0  | 405  | 0.7426          | 0.8667   |
| 0.0005        | 16.0  | 432  | 0.9776          | 0.8      |
| 0.0023        | 17.0  | 459  | 1.0180          | 0.8      |
| 0.0003        | 18.0  | 486  | 1.1105          | 0.7778   |
| 0.0006        | 19.0  | 513  | 0.9919          | 0.7556   |
| 0.0002        | 20.0  | 540  | 1.0177          | 0.8      |
| 0.0012        | 21.0  | 567  | 0.9992          | 0.8444   |
| 0.0003        | 22.0  | 594  | 0.9760          | 0.8444   |
| 0.0047        | 23.0  | 621  | 0.9891          | 0.8      |
| 0.0061        | 24.0  | 648  | 0.9730          | 0.8222   |
| 0.0002        | 25.0  | 675  | 0.8247          | 0.8222   |
| 0.0001        | 26.0  | 702  | 0.8270          | 0.8667   |
| 0.0001        | 27.0  | 729  | 0.7978          | 0.8222   |
| 0.0           | 28.0  | 756  | 0.8136          | 0.8444   |
| 0.0001        | 29.0  | 783  | 0.8553          | 0.8444   |
| 0.0001        | 30.0  | 810  | 0.9423          | 0.8444   |
| 0.0001        | 31.0  | 837  | 0.9286          | 0.8222   |
| 0.0001        | 32.0  | 864  | 0.9464          | 0.8222   |
| 0.0002        | 33.0  | 891  | 0.8713          | 0.8444   |
| 0.0001        | 34.0  | 918  | 0.8762          | 0.8444   |
| 0.0001        | 35.0  | 945  | 0.9092          | 0.8667   |
| 0.0           | 36.0  | 972  | 0.9547          | 0.8444   |
| 0.0           | 37.0  | 999  | 0.9283          | 0.8444   |
| 0.0           | 38.0  | 1026 | 0.8639          | 0.8444   |
| 0.0001        | 39.0  | 1053 | 0.8477          | 0.8667   |
| 0.0           | 40.0  | 1080 | 0.8432          | 0.8667   |
| 0.0           | 41.0  | 1107 | 0.8325          | 0.8667   |
| 0.0           | 42.0  | 1134 | 0.7851          | 0.8667   |
| 0.0003        | 43.0  | 1161 | 0.7875          | 0.8667   |
| 0.0           | 44.0  | 1188 | 0.7888          | 0.8667   |
| 0.0001        | 45.0  | 1215 | 0.8006          | 0.8889   |
| 0.0001        | 46.0  | 1242 | 0.8075          | 0.8889   |
| 0.0001        | 47.0  | 1269 | 0.8158          | 0.8889   |
| 0.0           | 48.0  | 1296 | 0.8184          | 0.8667   |
| 0.0002        | 49.0  | 1323 | 0.8184          | 0.8667   |
| 0.0001        | 50.0  | 1350 | 0.8184          | 0.8667   |


### Framework versions

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