---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: BEiT-RHS-NDA
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8317757009345794
---

<!-- 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. -->

# BEiT-RHS-NDA

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: 0.5322
- Accuracy: 0.8318

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 8    | 0.6851          | 0.5888   |
| 0.6911        | 2.0   | 16   | 0.6721          | 0.5888   |
| 0.6739        | 3.0   | 24   | 0.6504          | 0.5888   |
| 0.6595        | 4.0   | 32   | 0.6432          | 0.5888   |
| 0.646         | 5.0   | 40   | 0.6317          | 0.6822   |
| 0.646         | 6.0   | 48   | 0.6175          | 0.6916   |
| 0.6142        | 7.0   | 56   | 0.6270          | 0.6916   |
| 0.608         | 8.0   | 64   | 0.6618          | 0.6916   |
| 0.5927        | 9.0   | 72   | 0.5347          | 0.6916   |
| 0.5333        | 10.0  | 80   | 0.5744          | 0.6449   |
| 0.5333        | 11.0  | 88   | 0.4974          | 0.7477   |
| 0.4987        | 12.0  | 96   | 0.5970          | 0.6449   |
| 0.5421        | 13.0  | 104  | 0.5137          | 0.7383   |
| 0.4881        | 14.0  | 112  | 0.4727          | 0.7664   |
| 0.4408        | 15.0  | 120  | 0.5161          | 0.7664   |
| 0.4408        | 16.0  | 128  | 0.6732          | 0.6916   |
| 0.4923        | 17.0  | 136  | 0.6568          | 0.7009   |
| 0.4135        | 18.0  | 144  | 0.6653          | 0.7009   |
| 0.4308        | 19.0  | 152  | 0.6032          | 0.7196   |
| 0.3837        | 20.0  | 160  | 0.4492          | 0.8037   |
| 0.3837        | 21.0  | 168  | 0.4549          | 0.7944   |
| 0.3297        | 22.0  | 176  | 0.5526          | 0.7664   |
| 0.3264        | 23.0  | 184  | 0.5172          | 0.7944   |
| 0.3487        | 24.0  | 192  | 0.5105          | 0.7664   |
| 0.2892        | 25.0  | 200  | 0.4566          | 0.7757   |
| 0.2892        | 26.0  | 208  | 0.5233          | 0.7944   |
| 0.2505        | 27.0  | 216  | 0.4817          | 0.7944   |
| 0.2542        | 28.0  | 224  | 0.5035          | 0.8037   |
| 0.2285        | 29.0  | 232  | 0.5282          | 0.7944   |
| 0.2053        | 30.0  | 240  | 0.5638          | 0.8131   |
| 0.2053        | 31.0  | 248  | 0.6190          | 0.7570   |
| 0.2205        | 32.0  | 256  | 0.6142          | 0.7850   |
| 0.2081        | 33.0  | 264  | 0.5752          | 0.7850   |
| 0.2075        | 34.0  | 272  | 0.5322          | 0.8318   |
| 0.2286        | 35.0  | 280  | 0.5313          | 0.7944   |
| 0.2286        | 36.0  | 288  | 0.5189          | 0.8131   |
| 0.2008        | 37.0  | 296  | 0.5590          | 0.7850   |
| 0.1884        | 38.0  | 304  | 0.5488          | 0.7944   |
| 0.1819        | 39.0  | 312  | 0.5563          | 0.8037   |
| 0.1698        | 40.0  | 320  | 0.5679          | 0.7944   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0