---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: BEiT-DMAE-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: 0.8260869565217391
---

<!-- 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-DMAE-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: 0.5902
- Accuracy: 0.8261

## 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
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3475        | 0.96  | 11   | 1.3279          | 0.3261   |
| 1.1875        | 2.0   | 23   | 1.1320          | 0.3478   |
| 0.9998        | 2.96  | 34   | 0.9957          | 0.5435   |
| 0.8836        | 4.0   | 46   | 0.8436          | 0.5870   |
| 0.7593        | 4.96  | 57   | 0.7904          | 0.6304   |
| 0.6939        | 6.0   | 69   | 0.6656          | 0.8261   |
| 0.4924        | 6.96  | 80   | 0.6724          | 0.6739   |
| 0.4444        | 8.0   | 92   | 0.5951          | 0.7826   |
| 0.337         | 8.96  | 103  | 0.5222          | 0.8261   |
| 0.3213        | 10.0  | 115  | 0.6814          | 0.8043   |
| 0.2689        | 10.96 | 126  | 0.5913          | 0.7826   |
| 0.2538        | 12.0  | 138  | 0.6228          | 0.7826   |
| 0.2032        | 12.96 | 149  | 0.6992          | 0.7609   |
| 0.2152        | 14.0  | 161  | 0.7730          | 0.7609   |
| 0.1713        | 14.96 | 172  | 0.7762          | 0.7609   |
| 0.2042        | 16.0  | 184  | 0.7652          | 0.7174   |
| 0.1668        | 16.96 | 195  | 0.5512          | 0.8478   |
| 0.1743        | 18.0  | 207  | 0.7311          | 0.7826   |
| 0.1226        | 18.96 | 218  | 0.7115          | 0.8043   |
| 0.1537        | 20.0  | 230  | 0.6800          | 0.7609   |
| 0.1311        | 20.96 | 241  | 0.5864          | 0.8478   |
| 0.1335        | 22.0  | 253  | 0.6346          | 0.8261   |
| 0.0981        | 22.96 | 264  | 0.6541          | 0.8043   |
| 0.1248        | 24.0  | 276  | 0.7017          | 0.8261   |
| 0.1183        | 24.96 | 287  | 0.6964          | 0.8261   |
| 0.0946        | 26.0  | 299  | 0.6450          | 0.8261   |
| 0.0957        | 26.96 | 310  | 0.7057          | 0.8043   |
| 0.1692        | 28.0  | 322  | 0.6635          | 0.8043   |
| 0.0967        | 28.96 | 333  | 0.5040          | 0.8696   |
| 0.094         | 30.0  | 345  | 0.5588          | 0.8913   |
| 0.0843        | 30.96 | 356  | 0.5398          | 0.8696   |
| 0.0851        | 32.0  | 368  | 0.5806          | 0.8478   |
| 0.0955        | 32.96 | 379  | 0.4816          | 0.9130   |
| 0.1157        | 34.0  | 391  | 0.5289          | 0.8696   |
| 0.072         | 34.96 | 402  | 0.5657          | 0.8913   |
| 0.091         | 36.0  | 414  | 0.5566          | 0.8478   |
| 0.0891        | 36.96 | 425  | 0.5729          | 0.8478   |
| 0.0732        | 38.0  | 437  | 0.5915          | 0.8261   |
| 0.0647        | 38.26 | 440  | 0.5902          | 0.8261   |


### Framework versions

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