---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: BEiT-RD-DA
  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: 0.6654545454545454
---

<!-- 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-RD-DA

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: 1.9617
- Accuracy: 0.6655

## 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: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4123        | 1.0   | 96   | 1.4099          | 0.4927   |
| 0.9503        | 2.0   | 192  | 1.8852          | 0.4927   |
| 0.8284        | 3.0   | 288  | 2.1702          | 0.5073   |
| 0.7677        | 4.0   | 384  | 2.0408          | 0.5345   |
| 0.788         | 5.0   | 480  | 2.7991          | 0.5127   |
| 0.5822        | 6.0   | 576  | 2.0951          | 0.5636   |
| 0.5172        | 7.0   | 672  | 2.5977          | 0.5364   |
| 0.4615        | 8.0   | 768  | 2.0968          | 0.58     |
| 0.3672        | 9.0   | 864  | 2.8535          | 0.5436   |
| 0.379         | 10.0  | 960  | 2.9515          | 0.5382   |
| 0.3301        | 11.0  | 1056 | 2.7200          | 0.5582   |
| 0.2786        | 12.0  | 1152 | 1.9000          | 0.6273   |
| 0.2746        | 13.0  | 1248 | 3.1768          | 0.5364   |
| 0.2298        | 14.0  | 1344 | 3.1003          | 0.5527   |
| 0.2013        | 15.0  | 1440 | 2.3441          | 0.6182   |
| 0.2225        | 16.0  | 1536 | 3.0214          | 0.5709   |
| 0.2229        | 17.0  | 1632 | 2.0676          | 0.6164   |
| 0.2024        | 18.0  | 1728 | 2.6478          | 0.5673   |
| 0.1401        | 19.0  | 1824 | 2.8952          | 0.5636   |
| 0.1984        | 20.0  | 1920 | 2.3083          | 0.6145   |
| 0.1788        | 21.0  | 2016 | 3.7702          | 0.52     |
| 0.1907        | 22.0  | 2112 | 1.9617          | 0.6655   |
| 0.1113        | 23.0  | 2208 | 2.6546          | 0.5964   |
| 0.1293        | 24.0  | 2304 | 2.6427          | 0.6036   |
| 0.1354        | 25.0  | 2400 | 3.4105          | 0.5527   |
| 0.1447        | 26.0  | 2496 | 2.5460          | 0.6127   |
| 0.0995        | 27.0  | 2592 | 2.9865          | 0.5855   |
| 0.1369        | 28.0  | 2688 | 3.5281          | 0.5545   |
| 0.1238        | 29.0  | 2784 | 2.8161          | 0.6018   |
| 0.1256        | 30.0  | 2880 | 3.4917          | 0.5491   |
| 0.1064        | 31.0  | 2976 | 3.0659          | 0.58     |
| 0.1333        | 32.0  | 3072 | 3.5972          | 0.5473   |
| 0.1134        | 33.0  | 3168 | 3.6116          | 0.54     |
| 0.0831        | 34.0  | 3264 | 3.5308          | 0.5509   |
| 0.1035        | 35.0  | 3360 | 3.4789          | 0.5582   |
| 0.0957        | 36.0  | 3456 | 3.6358          | 0.5509   |
| 0.0764        | 37.0  | 3552 | 3.3639          | 0.5709   |
| 0.072         | 38.0  | 3648 | 3.5639          | 0.5564   |
| 0.0727        | 39.0  | 3744 | 3.5193          | 0.5582   |
| 0.0619        | 40.0  | 3840 | 3.5836          | 0.5582   |


### Framework versions

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