---
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_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: 0.8048780487804879
---

<!-- 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_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: 1.1845
- Accuracy: 0.8049

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9367        | 1.0   | 28   | 0.6533          | 0.7073   |
| 0.1926        | 2.0   | 56   | 0.5512          | 0.7805   |
| 0.047         | 3.0   | 84   | 0.6007          | 0.8049   |
| 0.0193        | 4.0   | 112  | 0.2590          | 0.9024   |
| 0.0089        | 5.0   | 140  | 0.4654          | 0.8293   |
| 0.0038        | 6.0   | 168  | 0.5932          | 0.8293   |
| 0.0017        | 7.0   | 196  | 0.6877          | 0.8293   |
| 0.0014        | 8.0   | 224  | 0.7982          | 0.8049   |
| 0.0007        | 9.0   | 252  | 0.6044          | 0.8293   |
| 0.0007        | 10.0  | 280  | 0.6788          | 0.8537   |
| 0.0003        | 11.0  | 308  | 0.6662          | 0.8537   |
| 0.0003        | 12.0  | 336  | 0.6588          | 0.8537   |
| 0.0002        | 13.0  | 364  | 0.6343          | 0.8293   |
| 0.0046        | 14.0  | 392  | 1.0649          | 0.7805   |
| 0.0012        | 15.0  | 420  | 0.7359          | 0.8293   |
| 0.0005        | 16.0  | 448  | 0.7345          | 0.8293   |
| 0.0066        | 17.0  | 476  | 0.7816          | 0.8537   |
| 0.0014        | 18.0  | 504  | 0.6553          | 0.8780   |
| 0.0003        | 19.0  | 532  | 0.5879          | 0.8780   |
| 0.0001        | 20.0  | 560  | 0.6539          | 0.8537   |
| 0.0001        | 21.0  | 588  | 0.5762          | 0.8293   |
| 0.0006        | 22.0  | 616  | 0.3307          | 0.8293   |
| 0.0001        | 23.0  | 644  | 0.6447          | 0.8293   |
| 0.0002        | 24.0  | 672  | 0.7471          | 0.8537   |
| 0.0002        | 25.0  | 700  | 0.6200          | 0.8537   |
| 0.0001        | 26.0  | 728  | 0.9057          | 0.8537   |
| 0.0001        | 27.0  | 756  | 0.8578          | 0.8537   |
| 0.0004        | 28.0  | 784  | 0.7354          | 0.8537   |
| 0.0001        | 29.0  | 812  | 0.8285          | 0.8537   |
| 0.0004        | 30.0  | 840  | 0.7442          | 0.8780   |
| 0.0001        | 31.0  | 868  | 0.9315          | 0.8049   |
| 0.0002        | 32.0  | 896  | 1.0255          | 0.8049   |
| 0.0           | 33.0  | 924  | 1.0401          | 0.7805   |
| 0.0001        | 34.0  | 952  | 1.0520          | 0.8293   |
| 0.0004        | 35.0  | 980  | 0.9869          | 0.8537   |
| 0.0           | 36.0  | 1008 | 0.9764          | 0.8537   |
| 0.0001        | 37.0  | 1036 | 0.9356          | 0.8537   |
| 0.0001        | 38.0  | 1064 | 1.1522          | 0.8049   |
| 0.0           | 39.0  | 1092 | 1.0978          | 0.8049   |
| 0.0005        | 40.0  | 1120 | 1.0647          | 0.8293   |
| 0.0003        | 41.0  | 1148 | 1.2331          | 0.8049   |
| 0.0           | 42.0  | 1176 | 1.3110          | 0.8049   |
| 0.0           | 43.0  | 1204 | 1.2050          | 0.8049   |
| 0.0           | 44.0  | 1232 | 1.1647          | 0.8049   |
| 0.0002        | 45.0  | 1260 | 1.2154          | 0.8049   |
| 0.0001        | 46.0  | 1288 | 1.2000          | 0.8049   |
| 0.0001        | 47.0  | 1316 | 1.1915          | 0.8049   |
| 0.0           | 48.0  | 1344 | 1.1844          | 0.8049   |
| 0.0001        | 49.0  | 1372 | 1.1845          | 0.8049   |
| 0.0           | 50.0  | 1400 | 1.1845          | 0.8049   |


### Framework versions

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