---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-DMAE-5e-5
  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: 0.8043478260869565
---

<!-- 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-base-patch16-224-DMAE-5e-5

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: 0.6236
- Accuracy: 0.8043

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.86  | 3    | 1.3816          | 0.4565   |
| No log        | 2.0   | 7    | 1.3504          | 0.4565   |
| 1.3654        | 2.86  | 10   | 1.3075          | 0.4565   |
| 1.3654        | 4.0   | 14   | 1.2444          | 0.4565   |
| 1.3654        | 4.86  | 17   | 1.2089          | 0.4565   |
| 1.2386        | 6.0   | 21   | 1.1711          | 0.4565   |
| 1.2386        | 6.86  | 24   | 1.1492          | 0.4565   |
| 1.2386        | 8.0   | 28   | 1.1050          | 0.4783   |
| 1.132         | 8.86  | 31   | 1.0928          | 0.6522   |
| 1.132         | 10.0  | 35   | 1.0230          | 0.6739   |
| 1.132         | 10.86 | 38   | 0.9864          | 0.6522   |
| 1.015         | 12.0  | 42   | 1.0060          | 0.6739   |
| 1.015         | 12.86 | 45   | 0.8790          | 0.7174   |
| 1.015         | 14.0  | 49   | 0.8533          | 0.6739   |
| 0.9217        | 14.86 | 52   | 0.8203          | 0.6957   |
| 0.9217        | 16.0  | 56   | 0.8152          | 0.6739   |
| 0.9217        | 16.86 | 59   | 0.8598          | 0.6522   |
| 0.7989        | 18.0  | 63   | 0.7979          | 0.6957   |
| 0.7989        | 18.86 | 66   | 0.7555          | 0.6739   |
| 0.7309        | 20.0  | 70   | 0.7019          | 0.7609   |
| 0.7309        | 20.86 | 73   | 0.7254          | 0.7174   |
| 0.7309        | 22.0  | 77   | 0.7268          | 0.6739   |
| 0.6267        | 22.86 | 80   | 0.7096          | 0.6739   |
| 0.6267        | 24.0  | 84   | 0.7568          | 0.6739   |
| 0.6267        | 24.86 | 87   | 0.6565          | 0.7391   |
| 0.564         | 26.0  | 91   | 0.7035          | 0.7391   |
| 0.564         | 26.86 | 94   | 0.7081          | 0.7391   |
| 0.564         | 28.0  | 98   | 0.6236          | 0.8043   |
| 0.5625        | 28.86 | 101  | 0.6091          | 0.8043   |
| 0.5625        | 30.0  | 105  | 0.6523          | 0.7609   |
| 0.5625        | 30.86 | 108  | 0.6235          | 0.7826   |
| 0.5185        | 32.0  | 112  | 0.5974          | 0.7826   |
| 0.5185        | 32.86 | 115  | 0.5944          | 0.7826   |
| 0.5185        | 34.0  | 119  | 0.6005          | 0.7826   |
| 0.5005        | 34.29 | 120  | 0.6005          | 0.7826   |


### Framework versions

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