---
library_name: transformers
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-humeda-DAV23
  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-humeda-DAV23

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: 0.6901
- Accuracy: 0.8118

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 6.4493        | 1.0     | 17   | 1.5281          | 0.2941   |
| 5.7922        | 2.0     | 34   | 1.3176          | 0.3882   |
| 4.2502        | 3.0     | 51   | 1.2015          | 0.4353   |
| 3.2402        | 4.0     | 68   | 0.8902          | 0.7176   |
| 2.5386        | 5.0     | 85   | 0.6509          | 0.7765   |
| 2.0351        | 6.0     | 102  | 0.6759          | 0.7647   |
| 1.8225        | 7.0     | 119  | 0.6607          | 0.7765   |
| 1.4778        | 8.0     | 136  | 0.7162          | 0.7529   |
| 1.4076        | 9.0     | 153  | 0.9084          | 0.7294   |
| 1.2056        | 10.0    | 170  | 0.6901          | 0.8118   |
| 0.9552        | 11.0    | 187  | 0.9153          | 0.7765   |
| 0.9859        | 12.0    | 204  | 0.8694          | 0.7529   |
| 0.8309        | 13.0    | 221  | 0.7666          | 0.8      |
| 0.7722        | 14.0    | 238  | 0.9118          | 0.7529   |
| 0.7632        | 15.0    | 255  | 0.8953          | 0.7529   |
| 0.5868        | 16.0    | 272  | 0.9678          | 0.7529   |
| 0.6577        | 17.0    | 289  | 1.0503          | 0.7765   |
| 0.5816        | 18.0    | 306  | 1.0602          | 0.7294   |
| 0.6222        | 19.0    | 323  | 1.1543          | 0.7765   |
| 0.4861        | 20.0    | 340  | 0.9739          | 0.8118   |
| 0.4422        | 21.0    | 357  | 1.0354          | 0.8      |
| 0.506         | 22.0    | 374  | 1.1097          | 0.8118   |
| 0.3833        | 23.0    | 391  | 1.2009          | 0.7765   |
| 0.4574        | 24.0    | 408  | 1.1366          | 0.7765   |
| 0.4467        | 25.0    | 425  | 1.0601          | 0.8118   |
| 0.4451        | 26.0    | 442  | 1.0935          | 0.7765   |
| 0.4384        | 27.0    | 459  | 1.1617          | 0.7647   |
| 0.4321        | 28.0    | 476  | 1.1012          | 0.7765   |
| 0.4398        | 29.0    | 493  | 1.0825          | 0.7882   |
| 0.361         | 30.0    | 510  | 1.1127          | 0.7647   |
| 0.4428        | 31.0    | 527  | 1.2024          | 0.7529   |
| 0.451         | 32.0    | 544  | 1.1550          | 0.7647   |
| 0.403         | 33.0    | 561  | 1.1646          | 0.7765   |
| 0.3059        | 34.0    | 578  | 1.2442          | 0.7765   |
| 0.3022        | 35.0    | 595  | 1.1976          | 0.7765   |
| 0.319         | 36.0    | 612  | 1.1564          | 0.7765   |
| 0.3737        | 37.0    | 629  | 1.1857          | 0.7765   |
| 0.3063        | 37.6667 | 640  | 1.1930          | 0.7765   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0