---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-dmae-va-U-40
  results: []
---

<!-- 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-va-U-40

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co./microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1175
- Accuracy: 0.9817

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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        | 0.9   | 7    | 1.3839          | 0.3028   |
| 1.4343        | 1.94  | 15   | 1.3643          | 0.2844   |
| 1.3413        | 2.97  | 23   | 1.3310          | 0.3578   |
| 1.2473        | 4.0   | 31   | 1.1081          | 0.5138   |
| 1.2473        | 4.9   | 38   | 0.8292          | 0.7064   |
| 1.0532        | 5.94  | 46   | 0.7420          | 0.6239   |
| 0.917         | 6.97  | 54   | 0.6345          | 0.6972   |
| 0.7939        | 8.0   | 62   | 0.4898          | 0.8532   |
| 0.7939        | 8.9   | 69   | 0.5918          | 0.7523   |
| 0.7457        | 9.94  | 77   | 0.5271          | 0.7615   |
| 0.6834        | 10.97 | 85   | 0.3296          | 0.9450   |
| 0.5847        | 12.0  | 93   | 0.2883          | 0.9174   |
| 0.5199        | 12.9  | 100  | 0.2896          | 0.9266   |
| 0.5199        | 13.94 | 108  | 0.2859          | 0.8991   |
| 0.4657        | 14.97 | 116  | 0.2515          | 0.9083   |
| 0.4585        | 16.0  | 124  | 0.2261          | 0.9083   |
| 0.3892        | 16.9  | 131  | 0.2142          | 0.9266   |
| 0.3892        | 17.94 | 139  | 0.1788          | 0.9450   |
| 0.3939        | 18.97 | 147  | 0.1948          | 0.9266   |
| 0.3429        | 20.0  | 155  | 0.1685          | 0.9450   |
| 0.3493        | 20.9  | 162  | 0.1986          | 0.9083   |
| 0.3462        | 21.94 | 170  | 0.1540          | 0.9358   |
| 0.3462        | 22.97 | 178  | 0.1449          | 0.9450   |
| 0.3117        | 24.0  | 186  | 0.1379          | 0.9541   |
| 0.3109        | 24.9  | 193  | 0.1423          | 0.9450   |
| 0.2867        | 25.94 | 201  | 0.1451          | 0.9450   |
| 0.2867        | 26.97 | 209  | 0.1154          | 0.9725   |
| 0.293         | 28.0  | 217  | 0.1152          | 0.9541   |
| 0.2782        | 28.9  | 224  | 0.1261          | 0.9633   |
| 0.2744        | 29.94 | 232  | 0.1175          | 0.9817   |
| 0.2711        | 30.97 | 240  | 0.1292          | 0.9633   |
| 0.2711        | 32.0  | 248  | 0.1101          | 0.9817   |
| 0.2652        | 32.9  | 255  | 0.1202          | 0.9633   |
| 0.2218        | 33.94 | 263  | 0.1119          | 0.9817   |
| 0.2899        | 34.97 | 271  | 0.1071          | 0.9817   |
| 0.2899        | 36.0  | 279  | 0.1077          | 0.9817   |
| 0.2143        | 36.13 | 280  | 0.1077          | 0.9817   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1