---
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-DAV41
  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-DAV41

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: 0.9385
- Accuracy: 0.6818

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- 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: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 1.4874          | 0.4318   |
| No log        | 2.0   | 4    | 1.3560          | 0.4432   |
| No log        | 3.0   | 6    | 1.3117          | 0.4432   |
| No log        | 4.0   | 8    | 1.2763          | 0.4432   |
| No log        | 5.0   | 10   | 1.2602          | 0.5682   |
| 8.9996        | 6.0   | 12   | 1.2348          | 0.6023   |
| 8.9996        | 7.0   | 14   | 1.1982          | 0.5795   |
| 8.9996        | 8.0   | 16   | 1.1592          | 0.6136   |
| 8.9996        | 9.0   | 18   | 1.1142          | 0.625    |
| 8.9996        | 10.0  | 20   | 1.0682          | 0.6364   |
| 8.9996        | 11.0  | 22   | 1.0256          | 0.6477   |
| 7.429         | 12.0  | 24   | 0.9843          | 0.6705   |
| 7.429         | 13.0  | 26   | 0.9602          | 0.6705   |
| 7.429         | 14.0  | 28   | 0.9452          | 0.6591   |
| 7.429         | 15.0  | 30   | 0.9385          | 0.6818   |
| 7.429         | 16.0  | 32   | 0.9320          | 0.6705   |
| 7.429         | 17.0  | 34   | 0.9285          | 0.6477   |
| 6.2752        | 18.0  | 36   | 0.9239          | 0.6591   |
| 6.2752        | 19.0  | 38   | 0.9214          | 0.6818   |
| 6.2752        | 20.0  | 40   | 0.9206          | 0.6818   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0