---
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_sgd_0001_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: 0.27906976744186046
---

<!-- 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_sgd_0001_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: 1.4647
- Accuracy: 0.2791

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5793        | 1.0   | 28   | 1.5789          | 0.2558   |
| 1.5183        | 2.0   | 56   | 1.5712          | 0.2558   |
| 1.5213        | 3.0   | 84   | 1.5641          | 0.2558   |
| 1.4605        | 4.0   | 112  | 1.5574          | 0.2558   |
| 1.4855        | 5.0   | 140  | 1.5511          | 0.2558   |
| 1.4714        | 6.0   | 168  | 1.5448          | 0.2558   |
| 1.5489        | 7.0   | 196  | 1.5392          | 0.2791   |
| 1.4903        | 8.0   | 224  | 1.5342          | 0.2791   |
| 1.4325        | 9.0   | 252  | 1.5290          | 0.2791   |
| 1.4353        | 10.0  | 280  | 1.5246          | 0.2558   |
| 1.4693        | 11.0  | 308  | 1.5207          | 0.2558   |
| 1.4343        | 12.0  | 336  | 1.5162          | 0.2558   |
| 1.4713        | 13.0  | 364  | 1.5122          | 0.2558   |
| 1.4732        | 14.0  | 392  | 1.5085          | 0.2558   |
| 1.517         | 15.0  | 420  | 1.5050          | 0.2558   |
| 1.4521        | 16.0  | 448  | 1.5018          | 0.2558   |
| 1.4309        | 17.0  | 476  | 1.4988          | 0.2558   |
| 1.4246        | 18.0  | 504  | 1.4964          | 0.2558   |
| 1.4231        | 19.0  | 532  | 1.4937          | 0.2558   |
| 1.4691        | 20.0  | 560  | 1.4912          | 0.2558   |
| 1.4305        | 21.0  | 588  | 1.4888          | 0.2558   |
| 1.4575        | 22.0  | 616  | 1.4865          | 0.2558   |
| 1.4268        | 23.0  | 644  | 1.4845          | 0.2558   |
| 1.3904        | 24.0  | 672  | 1.4827          | 0.2558   |
| 1.4432        | 25.0  | 700  | 1.4808          | 0.2558   |
| 1.4078        | 26.0  | 728  | 1.4793          | 0.2558   |
| 1.382         | 27.0  | 756  | 1.4777          | 0.2558   |
| 1.3894        | 28.0  | 784  | 1.4764          | 0.2558   |
| 1.4046        | 29.0  | 812  | 1.4751          | 0.2558   |
| 1.4273        | 30.0  | 840  | 1.4741          | 0.2791   |
| 1.3786        | 31.0  | 868  | 1.4730          | 0.2791   |
| 1.3777        | 32.0  | 896  | 1.4719          | 0.2791   |
| 1.3887        | 33.0  | 924  | 1.4708          | 0.2791   |
| 1.3651        | 34.0  | 952  | 1.4700          | 0.2791   |
| 1.4904        | 35.0  | 980  | 1.4692          | 0.2791   |
| 1.3288        | 36.0  | 1008 | 1.4686          | 0.2791   |
| 1.3653        | 37.0  | 1036 | 1.4680          | 0.2791   |
| 1.3833        | 38.0  | 1064 | 1.4673          | 0.2791   |
| 1.3973        | 39.0  | 1092 | 1.4668          | 0.2791   |
| 1.4044        | 40.0  | 1120 | 1.4663          | 0.2791   |
| 1.3896        | 41.0  | 1148 | 1.4659          | 0.2791   |
| 1.3676        | 42.0  | 1176 | 1.4656          | 0.2791   |
| 1.3444        | 43.0  | 1204 | 1.4654          | 0.2791   |
| 1.3782        | 44.0  | 1232 | 1.4651          | 0.2791   |
| 1.44          | 45.0  | 1260 | 1.4650          | 0.2791   |
| 1.383         | 46.0  | 1288 | 1.4648          | 0.2791   |
| 1.3752        | 47.0  | 1316 | 1.4648          | 0.2791   |
| 1.343         | 48.0  | 1344 | 1.4647          | 0.2791   |
| 1.3923        | 49.0  | 1372 | 1.4647          | 0.2791   |
| 1.429         | 50.0  | 1400 | 1.4647          | 0.2791   |


### Framework versions

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