---
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_fold4
  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: 0.9047619047619048
---

<!-- 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_fold4

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: 0.4242
- Accuracy: 0.9048

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7963        | 1.0   | 28   | 0.5873          | 0.8095   |
| 0.1378        | 2.0   | 56   | 0.2600          | 0.9048   |
| 0.0372        | 3.0   | 84   | 0.1249          | 0.9286   |
| 0.0142        | 4.0   | 112  | 0.1881          | 0.9048   |
| 0.0031        | 5.0   | 140  | 0.2720          | 0.9524   |
| 0.0011        | 6.0   | 168  | 0.2309          | 0.9286   |
| 0.0018        | 7.0   | 196  | 0.3809          | 0.9048   |
| 0.0008        | 8.0   | 224  | 0.3332          | 0.9048   |
| 0.0014        | 9.0   | 252  | 0.3365          | 0.8810   |
| 0.0123        | 10.0  | 280  | 0.2089          | 0.9286   |
| 0.0005        | 11.0  | 308  | 0.1962          | 0.9286   |
| 0.0038        | 12.0  | 336  | 0.2845          | 0.9048   |
| 0.0078        | 13.0  | 364  | 0.2498          | 0.9048   |
| 0.001         | 14.0  | 392  | 0.0353          | 1.0      |
| 0.0002        | 15.0  | 420  | 0.1604          | 0.9286   |
| 0.0003        | 16.0  | 448  | 0.6770          | 0.8810   |
| 0.0002        | 17.0  | 476  | 0.3566          | 0.9048   |
| 0.0001        | 18.0  | 504  | 0.1974          | 0.8810   |
| 0.0004        | 19.0  | 532  | 0.0247          | 1.0      |
| 0.0001        | 20.0  | 560  | 0.0905          | 0.9286   |
| 0.0001        | 21.0  | 588  | 0.1806          | 0.9286   |
| 0.0011        | 22.0  | 616  | 0.2156          | 0.9524   |
| 0.0007        | 23.0  | 644  | 0.4203          | 0.9286   |
| 0.0002        | 24.0  | 672  | 0.2731          | 0.9286   |
| 0.0054        | 25.0  | 700  | 0.2589          | 0.8810   |
| 0.0001        | 26.0  | 728  | 0.2893          | 0.9048   |
| 0.0           | 27.0  | 756  | 0.3737          | 0.8810   |
| 0.0002        | 28.0  | 784  | 0.3310          | 0.9048   |
| 0.0001        | 29.0  | 812  | 0.2394          | 0.9048   |
| 0.0           | 30.0  | 840  | 0.2320          | 0.9048   |
| 0.0001        | 31.0  | 868  | 0.2751          | 0.9048   |
| 0.0012        | 32.0  | 896  | 0.2756          | 0.9048   |
| 0.0           | 33.0  | 924  | 0.1983          | 0.9048   |
| 0.0001        | 34.0  | 952  | 0.1565          | 0.9048   |
| 0.0           | 35.0  | 980  | 0.1912          | 0.9048   |
| 0.0001        | 36.0  | 1008 | 0.2103          | 0.9048   |
| 0.0           | 37.0  | 1036 | 0.1693          | 0.9048   |
| 0.0           | 38.0  | 1064 | 0.1895          | 0.9048   |
| 0.0           | 39.0  | 1092 | 0.2300          | 0.9048   |
| 0.0018        | 40.0  | 1120 | 0.7391          | 0.9048   |
| 0.0           | 41.0  | 1148 | 0.6660          | 0.9048   |
| 0.0           | 42.0  | 1176 | 0.5981          | 0.9048   |
| 0.0001        | 43.0  | 1204 | 0.6379          | 0.9048   |
| 0.0001        | 44.0  | 1232 | 0.5736          | 0.9048   |
| 0.0002        | 45.0  | 1260 | 0.4940          | 0.9048   |
| 0.0001        | 46.0  | 1288 | 0.4348          | 0.9048   |
| 0.0001        | 47.0  | 1316 | 0.4551          | 0.9048   |
| 0.0           | 48.0  | 1344 | 0.4241          | 0.9048   |
| 0.0026        | 49.0  | 1372 | 0.4242          | 0.9048   |
| 0.0           | 50.0  | 1400 | 0.4242          | 0.9048   |


### Framework versions

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