---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: BEiT-RHS-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: 0.6355140186915887
---

<!-- 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-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: 1.7194
- Accuracy: 0.6355

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2357        | 0.98  | 22   | 0.7114          | 0.5888   |
| 0.6596        | 2.0   | 45   | 0.7059          | 0.5981   |
| 0.206         | 2.98  | 67   | 1.1449          | 0.5981   |
| 0.1664        | 4.0   | 90   | 2.2062          | 0.3925   |
| 0.1011        | 4.98  | 112  | 2.0409          | 0.4673   |
| 0.0653        | 6.0   | 135  | 1.3038          | 0.6262   |
| 0.2843        | 6.98  | 157  | 1.7210          | 0.5981   |
| 0.059         | 8.0   | 180  | 2.8706          | 0.4673   |
| 0.1318        | 8.98  | 202  | 2.4519          | 0.5888   |
| 0.0501        | 10.0  | 225  | 2.2037          | 0.5888   |
| 0.054         | 10.98 | 247  | 2.6467          | 0.5888   |
| 0.0263        | 12.0  | 270  | 2.4033          | 0.5981   |
| 0.0553        | 12.98 | 292  | 1.6589          | 0.5888   |
| 0.0898        | 14.0  | 315  | 1.7657          | 0.5981   |
| 0.0324        | 14.98 | 337  | 2.8266          | 0.5888   |
| 0.0322        | 16.0  | 360  | 1.7194          | 0.6355   |
| 0.03          | 16.98 | 382  | 2.0352          | 0.6168   |
| 0.0392        | 18.0  | 405  | 2.4130          | 0.6168   |
| 0.0428        | 18.98 | 427  | 2.0628          | 0.6075   |
| 0.0127        | 20.0  | 450  | 2.7431          | 0.5888   |
| 0.0187        | 20.98 | 472  | 2.7009          | 0.5981   |
| 0.0469        | 22.0  | 495  | 2.5783          | 0.5981   |
| 0.0095        | 22.98 | 517  | 2.3040          | 0.5981   |
| 0.0025        | 24.0  | 540  | 2.5218          | 0.6168   |
| 0.0281        | 24.98 | 562  | 3.2310          | 0.5981   |
| 0.0004        | 26.0  | 585  | 3.2731          | 0.5981   |
| 0.0109        | 26.98 | 607  | 2.4809          | 0.6262   |
| 0.0191        | 28.0  | 630  | 2.7825          | 0.5888   |
| 0.0005        | 28.98 | 652  | 3.5280          | 0.5888   |
| 0.0093        | 30.0  | 675  | 2.8290          | 0.6075   |
| 0.0224        | 30.98 | 697  | 2.9546          | 0.5794   |
| 0.0011        | 32.0  | 720  | 3.0148          | 0.6075   |
| 0.003         | 32.98 | 742  | 3.2916          | 0.5981   |
| 0.0003        | 34.0  | 765  | 3.2930          | 0.5981   |
| 0.0003        | 34.98 | 787  | 3.6287          | 0.5888   |
| 0.0002        | 36.0  | 810  | 3.6918          | 0.5888   |
| 0.0004        | 36.98 | 832  | 3.6597          | 0.5888   |
| 0.0003        | 38.0  | 855  | 3.6599          | 0.5888   |
| 0.0002        | 38.98 | 877  | 3.6740          | 0.5888   |
| 0.0002        | 39.11 | 880  | 3.6741          | 0.5888   |


### Framework versions

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