---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-DMAE-5e-1
  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: 0.45652173913043476
---

<!-- 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. -->

# swinv2-tiny-patch4-window8-256-DMAE-5e-1

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 54.3349
- Accuracy: 0.4565

## 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: 0.5
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.86  | 3    | 343.8003        | 0.3261   |
| No log        | 2.0   | 7    | 1260.1489       | 0.1087   |
| 517.6714      | 2.86  | 10   | 457.5103        | 0.3261   |
| 517.6714      | 4.0   | 14   | 180.1205        | 0.1087   |
| 517.6714      | 4.86  | 17   | 190.9627        | 0.1087   |
| 201.7487      | 6.0   | 21   | 54.3349         | 0.4565   |
| 201.7487      | 6.86  | 24   | 70.2849         | 0.3261   |
| 201.7487      | 8.0   | 28   | 57.7033         | 0.3261   |
| 64.7194       | 8.86  | 31   | 115.5257        | 0.1087   |
| 64.7194       | 10.0  | 35   | 72.7990         | 0.3261   |
| 64.7194       | 10.86 | 38   | 41.8670         | 0.4565   |
| 58.6249       | 12.0  | 42   | 26.2765         | 0.4565   |
| 58.6249       | 12.86 | 45   | 41.7245         | 0.3261   |
| 58.6249       | 14.0  | 49   | 23.6962         | 0.4565   |
| 49.7372       | 14.86 | 52   | 13.4265         | 0.3261   |
| 49.7372       | 16.0  | 56   | 7.0405          | 0.4565   |
| 49.7372       | 16.86 | 59   | 5.0777          | 0.4565   |
| 11.7669       | 18.0  | 63   | 13.5690         | 0.4565   |
| 11.7669       | 18.86 | 66   | 5.5425          | 0.1087   |
| 13.3323       | 20.0  | 70   | 6.4491          | 0.4565   |
| 13.3323       | 20.86 | 73   | 7.3066          | 0.3261   |
| 13.3323       | 22.0  | 77   | 10.8431         | 0.4565   |
| 9.2763        | 22.86 | 80   | 12.1588         | 0.3261   |
| 9.2763        | 24.0  | 84   | 5.4926          | 0.4565   |
| 9.2763        | 24.86 | 87   | 4.4689          | 0.3261   |
| 6.8526        | 26.0  | 91   | 3.7880          | 0.4565   |
| 6.8526        | 26.86 | 94   | 2.3297          | 0.4565   |
| 6.8526        | 28.0  | 98   | 2.8532          | 0.4565   |
| 3.0687        | 28.86 | 101  | 2.6943          | 0.1087   |
| 3.0687        | 30.0  | 105  | 2.0957          | 0.3261   |
| 3.0687        | 30.86 | 108  | 1.4001          | 0.4565   |
| 2.1059        | 32.0  | 112  | 1.3081          | 0.3261   |
| 2.1059        | 32.86 | 115  | 1.2392          | 0.3261   |
| 2.1059        | 34.0  | 119  | 1.2510          | 0.4565   |
| 1.3417        | 34.29 | 120  | 1.2338          | 0.4565   |


### Framework versions

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