---
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
  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: 0.7608695652173914
---

<!-- 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

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: 0.6703
- Accuracy: 0.7609

## 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: 0.00015
- 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    | 1.3117          | 0.4565   |
| No log        | 2.0   | 7    | 1.2539          | 0.4565   |
| 1.2875        | 2.86  | 10   | 1.2355          | 0.4565   |
| 1.2875        | 4.0   | 14   | 1.1827          | 0.4783   |
| 1.2875        | 4.86  | 17   | 1.0758          | 0.6522   |
| 1.1369        | 6.0   | 21   | 1.0942          | 0.5      |
| 1.1369        | 6.86  | 24   | 1.1312          | 0.5217   |
| 1.1369        | 8.0   | 28   | 1.0906          | 0.5217   |
| 1.1009        | 8.86  | 31   | 0.8704          | 0.6957   |
| 1.1009        | 10.0  | 35   | 1.0023          | 0.5870   |
| 1.1009        | 10.86 | 38   | 1.0288          | 0.5870   |
| 0.9152        | 12.0  | 42   | 0.7874          | 0.7174   |
| 0.9152        | 12.86 | 45   | 0.7166          | 0.7174   |
| 0.9152        | 14.0  | 49   | 0.7269          | 0.6957   |
| 0.8444        | 14.86 | 52   | 0.8481          | 0.6957   |
| 0.8444        | 16.0  | 56   | 0.7589          | 0.6304   |
| 0.8444        | 16.86 | 59   | 0.7590          | 0.6304   |
| 0.8085        | 18.0  | 63   | 0.8320          | 0.6304   |
| 0.8085        | 18.86 | 66   | 0.7469          | 0.7391   |
| 0.6941        | 20.0  | 70   | 0.8337          | 0.6304   |
| 0.6941        | 20.86 | 73   | 0.7928          | 0.7174   |
| 0.6941        | 22.0  | 77   | 0.8765          | 0.6522   |
| 0.5822        | 22.86 | 80   | 0.7139          | 0.7174   |
| 0.5822        | 24.0  | 84   | 0.7477          | 0.6957   |
| 0.5822        | 24.86 | 87   | 0.6987          | 0.7174   |
| 0.5174        | 26.0  | 91   | 0.6815          | 0.7391   |
| 0.5174        | 26.86 | 94   | 0.7332          | 0.7174   |
| 0.5174        | 28.0  | 98   | 0.6582          | 0.7391   |
| 0.48          | 28.86 | 101  | 0.7273          | 0.7391   |
| 0.48          | 30.0  | 105  | 0.7595          | 0.6957   |
| 0.48          | 30.86 | 108  | 0.7136          | 0.7391   |
| 0.4159        | 32.0  | 112  | 0.6703          | 0.7609   |
| 0.4159        | 32.86 | 115  | 0.6736          | 0.7609   |
| 0.4159        | 34.0  | 119  | 0.6866          | 0.7609   |
| 0.3472        | 34.29 | 120  | 0.6873          | 0.7609   |


### Framework versions

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