---
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-U5-42B
  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-U5-42B

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: 1.0633
- Accuracy: 0.6333

## 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: 4e-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: 42

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 7.8663          | 0.1167   |
| 6.936         | 1.94  | 15   | 7.7572          | 0.1167   |
| 6.936         | 2.97  | 23   | 7.1789          | 0.1167   |
| 6.7016        | 4.0   | 31   | 5.9142          | 0.1167   |
| 5.5418        | 4.9   | 38   | 4.6065          | 0.1167   |
| 5.5418        | 5.94  | 46   | 3.2783          | 0.1167   |
| 3.6439        | 6.97  | 54   | 2.1984          | 0.1167   |
| 2.2477        | 8.0   | 62   | 1.5631          | 0.45     |
| 2.2477        | 8.9   | 69   | 1.3158          | 0.45     |
| 1.5076        | 9.94  | 77   | 1.3665          | 0.3333   |
| 1.3865        | 10.97 | 85   | 1.3561          | 0.35     |
| 1.3865        | 12.0  | 93   | 1.2673          | 0.4667   |
| 1.3436        | 12.9  | 100  | 1.5020          | 0.2833   |
| 1.3187        | 13.94 | 108  | 1.3018          | 0.4667   |
| 1.3187        | 14.97 | 116  | 1.2582          | 0.4833   |
| 1.2132        | 16.0  | 124  | 1.2250          | 0.5      |
| 1.2132        | 16.9  | 131  | 1.2071          | 0.5167   |
| 1.2041        | 17.94 | 139  | 1.1806          | 0.5167   |
| 1.1756        | 18.97 | 147  | 1.1720          | 0.55     |
| 1.1756        | 20.0  | 155  | 1.1319          | 0.5333   |
| 1.1107        | 20.9  | 162  | 1.0851          | 0.5833   |
| 1.0651        | 21.94 | 170  | 1.0554          | 0.5833   |
| 1.0651        | 22.97 | 178  | 1.0580          | 0.5      |
| 1.0419        | 24.0  | 186  | 1.1471          | 0.5833   |
| 0.9804        | 24.9  | 193  | 1.0633          | 0.6333   |
| 0.9804        | 25.94 | 201  | 1.0597          | 0.5833   |
| 0.9195        | 26.97 | 209  | 0.9563          | 0.6333   |
| 0.9053        | 28.0  | 217  | 0.9839          | 0.5167   |
| 0.9053        | 28.9  | 224  | 0.9914          | 0.5167   |
| 0.8645        | 29.94 | 232  | 0.9520          | 0.5833   |
| 0.8139        | 30.97 | 240  | 0.9573          | 0.5333   |
| 0.8139        | 32.0  | 248  | 0.9510          | 0.5167   |
| 0.8151        | 32.9  | 255  | 0.9469          | 0.5167   |
| 0.8151        | 33.94 | 263  | 0.9872          | 0.5333   |
| 0.7837        | 34.97 | 271  | 0.9279          | 0.5833   |
| 0.7659        | 36.0  | 279  | 0.9174          | 0.5667   |
| 0.7659        | 36.9  | 286  | 0.9347          | 0.5667   |
| 0.7835        | 37.94 | 294  | 0.9372          | 0.5667   |


### Framework versions

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