---
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_fold1
  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: 0.8222222222222222
---

<!-- 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_fold1

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: 0.5839
- Accuracy: 0.8222

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5474        | 1.0   | 27   | 0.5910          | 0.8444   |
| 0.0818        | 2.0   | 54   | 0.5720          | 0.7778   |
| 0.0238        | 3.0   | 81   | 0.8576          | 0.7111   |
| 0.0074        | 4.0   | 108  | 0.5321          | 0.8667   |
| 0.0032        | 5.0   | 135  | 0.4605          | 0.8667   |
| 0.0017        | 6.0   | 162  | 0.6849          | 0.7778   |
| 0.0024        | 7.0   | 189  | 0.4973          | 0.8667   |
| 0.0008        | 8.0   | 216  | 0.4640          | 0.8667   |
| 0.0044        | 9.0   | 243  | 0.6817          | 0.8222   |
| 0.0005        | 10.0  | 270  | 0.5671          | 0.8222   |
| 0.0004        | 11.0  | 297  | 0.5195          | 0.8444   |
| 0.0002        | 12.0  | 324  | 0.7506          | 0.8222   |
| 0.0007        | 13.0  | 351  | 0.4960          | 0.8667   |
| 0.0004        | 14.0  | 378  | 0.4879          | 0.8667   |
| 0.0002        | 15.0  | 405  | 0.2878          | 0.8889   |
| 0.0004        | 16.0  | 432  | 0.5723          | 0.7778   |
| 0.0038        | 17.0  | 459  | 0.8796          | 0.8      |
| 0.0011        | 18.0  | 486  | 0.4544          | 0.8444   |
| 0.001         | 19.0  | 513  | 0.2346          | 0.8889   |
| 0.0001        | 20.0  | 540  | 0.6421          | 0.8444   |
| 0.0001        | 21.0  | 567  | 0.5172          | 0.8667   |
| 0.0012        | 22.0  | 594  | 0.4729          | 0.8222   |
| 0.0001        | 23.0  | 621  | 0.4318          | 0.8222   |
| 0.0001        | 24.0  | 648  | 0.4087          | 0.8222   |
| 0.0004        | 25.0  | 675  | 0.4267          | 0.8889   |
| 0.0001        | 26.0  | 702  | 0.4250          | 0.8667   |
| 0.0001        | 27.0  | 729  | 0.3081          | 0.8889   |
| 0.0001        | 28.0  | 756  | 0.4008          | 0.8222   |
| 0.0           | 29.0  | 783  | 0.3766          | 0.8444   |
| 0.0001        | 30.0  | 810  | 0.3622          | 0.9111   |
| 0.0           | 31.0  | 837  | 0.4006          | 0.8222   |
| 0.0001        | 32.0  | 864  | 0.4743          | 0.8444   |
| 0.0001        | 33.0  | 891  | 0.3292          | 0.8889   |
| 0.0001        | 34.0  | 918  | 1.1554          | 0.7556   |
| 0.0002        | 35.0  | 945  | 0.6888          | 0.8      |
| 0.0003        | 36.0  | 972  | 0.4504          | 0.8667   |
| 0.0001        | 37.0  | 999  | 0.4287          | 0.8667   |
| 0.0           | 38.0  | 1026 | 0.4528          | 0.8667   |
| 0.0001        | 39.0  | 1053 | 0.4353          | 0.8667   |
| 0.0           | 40.0  | 1080 | 0.4656          | 0.8444   |
| 0.0044        | 41.0  | 1107 | 0.4571          | 0.8222   |
| 0.0           | 42.0  | 1134 | 0.4813          | 0.8222   |
| 0.0004        | 43.0  | 1161 | 0.5618          | 0.8444   |
| 0.0           | 44.0  | 1188 | 0.5635          | 0.8444   |
| 0.0           | 45.0  | 1215 | 0.5635          | 0.8444   |
| 0.0061        | 46.0  | 1242 | 0.5733          | 0.8444   |
| 0.0           | 47.0  | 1269 | 0.5697          | 0.8444   |
| 0.0001        | 48.0  | 1296 | 0.5838          | 0.8222   |
| 0.0001        | 49.0  | 1323 | 0.5839          | 0.8222   |
| 0.0           | 50.0  | 1350 | 0.5839          | 0.8222   |


### Framework versions

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