---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_beit_base_rms_0001_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: 0.4222222222222222
---

<!-- 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_1x_beit_base_rms_0001_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: 1.7892
- Accuracy: 0.4222

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.3881          | 0.2444   |
| 1.983         | 2.0   | 12   | 1.4040          | 0.2444   |
| 1.983         | 3.0   | 18   | 1.4052          | 0.2667   |
| 1.41          | 4.0   | 24   | 1.3851          | 0.2444   |
| 1.3993        | 5.0   | 30   | 1.3596          | 0.2667   |
| 1.3993        | 6.0   | 36   | 1.5010          | 0.2444   |
| 1.3135        | 7.0   | 42   | 1.4385          | 0.3778   |
| 1.3135        | 8.0   | 48   | 1.3273          | 0.2222   |
| 1.2878        | 9.0   | 54   | 1.7515          | 0.2444   |
| 1.2036        | 10.0  | 60   | 1.4739          | 0.3111   |
| 1.2036        | 11.0  | 66   | 1.4793          | 0.4444   |
| 1.1544        | 12.0  | 72   | 1.6976          | 0.4444   |
| 1.1544        | 13.0  | 78   | 1.5051          | 0.3778   |
| 1.1611        | 14.0  | 84   | 2.0887          | 0.2444   |
| 1.0944        | 15.0  | 90   | 1.7507          | 0.3778   |
| 1.0944        | 16.0  | 96   | 1.5983          | 0.4      |
| 1.1053        | 17.0  | 102  | 1.5239          | 0.3333   |
| 1.1053        | 18.0  | 108  | 1.7239          | 0.3333   |
| 0.9531        | 19.0  | 114  | 1.7796          | 0.3778   |
| 0.9208        | 20.0  | 120  | 1.7000          | 0.4      |
| 0.9208        | 21.0  | 126  | 1.5682          | 0.3556   |
| 0.9119        | 22.0  | 132  | 1.6947          | 0.2889   |
| 0.9119        | 23.0  | 138  | 1.9309          | 0.3111   |
| 0.8438        | 24.0  | 144  | 1.7778          | 0.4      |
| 0.7982        | 25.0  | 150  | 1.3358          | 0.4889   |
| 0.7982        | 26.0  | 156  | 1.8930          | 0.3778   |
| 0.7528        | 27.0  | 162  | 1.5978          | 0.4444   |
| 0.7528        | 28.0  | 168  | 1.7048          | 0.4      |
| 0.7372        | 29.0  | 174  | 1.4976          | 0.4      |
| 0.6872        | 30.0  | 180  | 1.5193          | 0.4222   |
| 0.6872        | 31.0  | 186  | 1.5712          | 0.3778   |
| 0.6257        | 32.0  | 192  | 1.6492          | 0.4      |
| 0.6257        | 33.0  | 198  | 1.6572          | 0.4444   |
| 0.6115        | 34.0  | 204  | 1.7617          | 0.4222   |
| 0.502         | 35.0  | 210  | 1.7836          | 0.4      |
| 0.502         | 36.0  | 216  | 1.7245          | 0.4222   |
| 0.5351        | 37.0  | 222  | 1.8523          | 0.3778   |
| 0.5351        | 38.0  | 228  | 1.8752          | 0.3778   |
| 0.4239        | 39.0  | 234  | 1.7739          | 0.4222   |
| 0.4397        | 40.0  | 240  | 1.8121          | 0.4      |
| 0.4397        | 41.0  | 246  | 1.7942          | 0.4222   |
| 0.3888        | 42.0  | 252  | 1.7892          | 0.4222   |
| 0.3888        | 43.0  | 258  | 1.7892          | 0.4222   |
| 0.3836        | 44.0  | 264  | 1.7892          | 0.4222   |
| 0.3564        | 45.0  | 270  | 1.7892          | 0.4222   |
| 0.3564        | 46.0  | 276  | 1.7892          | 0.4222   |
| 0.3801        | 47.0  | 282  | 1.7892          | 0.4222   |
| 0.3801        | 48.0  | 288  | 1.7892          | 0.4222   |
| 0.316         | 49.0  | 294  | 1.7892          | 0.4222   |
| 0.3933        | 50.0  | 300  | 1.7892          | 0.4222   |


### Framework versions

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