---
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_sgd_001_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: 0.43902439024390244
---

<!-- 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_sgd_001_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: 1.3101
- Accuracy: 0.4390

## 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: 0.001
- 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    | 1.5856          | 0.2439   |
| 1.5446        | 2.0   | 12   | 1.5524          | 0.2683   |
| 1.5446        | 3.0   | 18   | 1.5246          | 0.3171   |
| 1.4921        | 4.0   | 24   | 1.5015          | 0.3171   |
| 1.4491        | 5.0   | 30   | 1.4859          | 0.3415   |
| 1.4491        | 6.0   | 36   | 1.4721          | 0.3415   |
| 1.4253        | 7.0   | 42   | 1.4615          | 0.3415   |
| 1.4253        | 8.0   | 48   | 1.4471          | 0.3659   |
| 1.3656        | 9.0   | 54   | 1.4347          | 0.3902   |
| 1.3889        | 10.0  | 60   | 1.4270          | 0.3902   |
| 1.3889        | 11.0  | 66   | 1.4192          | 0.4146   |
| 1.3303        | 12.0  | 72   | 1.4108          | 0.4146   |
| 1.3303        | 13.0  | 78   | 1.4040          | 0.4146   |
| 1.3227        | 14.0  | 84   | 1.3958          | 0.4146   |
| 1.3003        | 15.0  | 90   | 1.3889          | 0.4146   |
| 1.3003        | 16.0  | 96   | 1.3827          | 0.4146   |
| 1.3072        | 17.0  | 102  | 1.3788          | 0.3902   |
| 1.3072        | 18.0  | 108  | 1.3733          | 0.4146   |
| 1.2978        | 19.0  | 114  | 1.3664          | 0.4390   |
| 1.268         | 20.0  | 120  | 1.3623          | 0.4390   |
| 1.268         | 21.0  | 126  | 1.3569          | 0.4390   |
| 1.265         | 22.0  | 132  | 1.3511          | 0.4390   |
| 1.265         | 23.0  | 138  | 1.3470          | 0.4634   |
| 1.2559        | 24.0  | 144  | 1.3424          | 0.4390   |
| 1.2443        | 25.0  | 150  | 1.3395          | 0.4146   |
| 1.2443        | 26.0  | 156  | 1.3357          | 0.4390   |
| 1.2468        | 27.0  | 162  | 1.3318          | 0.4390   |
| 1.2468        | 28.0  | 168  | 1.3281          | 0.4390   |
| 1.2381        | 29.0  | 174  | 1.3262          | 0.4390   |
| 1.2466        | 30.0  | 180  | 1.3249          | 0.4146   |
| 1.2466        | 31.0  | 186  | 1.3215          | 0.4390   |
| 1.234         | 32.0  | 192  | 1.3185          | 0.4390   |
| 1.234         | 33.0  | 198  | 1.3170          | 0.4390   |
| 1.2144        | 34.0  | 204  | 1.3158          | 0.4390   |
| 1.2407        | 35.0  | 210  | 1.3143          | 0.4390   |
| 1.2407        | 36.0  | 216  | 1.3132          | 0.4390   |
| 1.2238        | 37.0  | 222  | 1.3125          | 0.4390   |
| 1.2238        | 38.0  | 228  | 1.3116          | 0.4390   |
| 1.221         | 39.0  | 234  | 1.3110          | 0.4390   |
| 1.1985        | 40.0  | 240  | 1.3104          | 0.4390   |
| 1.1985        | 41.0  | 246  | 1.3101          | 0.4390   |
| 1.2078        | 42.0  | 252  | 1.3101          | 0.4390   |
| 1.2078        | 43.0  | 258  | 1.3101          | 0.4390   |
| 1.1965        | 44.0  | 264  | 1.3101          | 0.4390   |
| 1.2151        | 45.0  | 270  | 1.3101          | 0.4390   |
| 1.2151        | 46.0  | 276  | 1.3101          | 0.4390   |
| 1.2187        | 47.0  | 282  | 1.3101          | 0.4390   |
| 1.2187        | 48.0  | 288  | 1.3101          | 0.4390   |
| 1.1908        | 49.0  | 294  | 1.3101          | 0.4390   |
| 1.1985        | 50.0  | 300  | 1.3101          | 0.4390   |


### Framework versions

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