---
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_adamax_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: 0.8604651162790697
---

<!-- 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_adamax_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: 0.5855
- Accuracy: 0.8605

## 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    | 1.0849          | 0.5349   |
| 1.2852        | 2.0   | 12   | 0.7460          | 0.7907   |
| 1.2852        | 3.0   | 18   | 0.5699          | 0.8140   |
| 0.4305        | 4.0   | 24   | 0.3649          | 0.8605   |
| 0.1805        | 5.0   | 30   | 0.2406          | 0.9535   |
| 0.1805        | 6.0   | 36   | 0.4656          | 0.8837   |
| 0.0211        | 7.0   | 42   | 0.4915          | 0.8605   |
| 0.0211        | 8.0   | 48   | 0.5042          | 0.8372   |
| 0.0066        | 9.0   | 54   | 0.6760          | 0.7907   |
| 0.0025        | 10.0  | 60   | 0.6098          | 0.8605   |
| 0.0025        | 11.0  | 66   | 0.6353          | 0.9070   |
| 0.0011        | 12.0  | 72   | 0.6882          | 0.8837   |
| 0.0011        | 13.0  | 78   | 0.6437          | 0.8837   |
| 0.0022        | 14.0  | 84   | 0.5430          | 0.8605   |
| 0.0007        | 15.0  | 90   | 0.5436          | 0.8605   |
| 0.0007        | 16.0  | 96   | 0.5847          | 0.8605   |
| 0.0007        | 17.0  | 102  | 0.7054          | 0.8605   |
| 0.0007        | 18.0  | 108  | 0.7624          | 0.8372   |
| 0.0006        | 19.0  | 114  | 0.6619          | 0.8605   |
| 0.0007        | 20.0  | 120  | 0.6238          | 0.8372   |
| 0.0007        | 21.0  | 126  | 0.6086          | 0.8372   |
| 0.0003        | 22.0  | 132  | 0.6074          | 0.8372   |
| 0.0003        | 23.0  | 138  | 0.6228          | 0.8605   |
| 0.0003        | 24.0  | 144  | 0.6265          | 0.8605   |
| 0.0003        | 25.0  | 150  | 0.6139          | 0.8372   |
| 0.0003        | 26.0  | 156  | 0.6063          | 0.8372   |
| 0.0002        | 27.0  | 162  | 0.5981          | 0.8372   |
| 0.0002        | 28.0  | 168  | 0.5901          | 0.8372   |
| 0.0002        | 29.0  | 174  | 0.5785          | 0.8605   |
| 0.0001        | 30.0  | 180  | 0.5753          | 0.8605   |
| 0.0001        | 31.0  | 186  | 0.5775          | 0.8605   |
| 0.0002        | 32.0  | 192  | 0.5781          | 0.8605   |
| 0.0002        | 33.0  | 198  | 0.5782          | 0.8605   |
| 0.0002        | 34.0  | 204  | 0.5804          | 0.8605   |
| 0.0003        | 35.0  | 210  | 0.5817          | 0.8605   |
| 0.0003        | 36.0  | 216  | 0.5823          | 0.8605   |
| 0.0001        | 37.0  | 222  | 0.5831          | 0.8605   |
| 0.0001        | 38.0  | 228  | 0.5855          | 0.8605   |
| 0.0002        | 39.0  | 234  | 0.5859          | 0.8605   |
| 0.0002        | 40.0  | 240  | 0.5858          | 0.8605   |
| 0.0002        | 41.0  | 246  | 0.5855          | 0.8605   |
| 0.0002        | 42.0  | 252  | 0.5855          | 0.8605   |
| 0.0002        | 43.0  | 258  | 0.5855          | 0.8605   |
| 0.0002        | 44.0  | 264  | 0.5855          | 0.8605   |
| 0.0001        | 45.0  | 270  | 0.5855          | 0.8605   |
| 0.0001        | 46.0  | 276  | 0.5855          | 0.8605   |
| 0.0005        | 47.0  | 282  | 0.5855          | 0.8605   |
| 0.0005        | 48.0  | 288  | 0.5855          | 0.8605   |
| 0.0002        | 49.0  | 294  | 0.5855          | 0.8605   |
| 0.0001        | 50.0  | 300  | 0.5855          | 0.8605   |


### Framework versions

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