
<!-- 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-finetuned-validshop-car-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2577
- Accuracy: 0.8915

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use 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: 6

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.9275        | 1.0    | 37   | 0.2632          | 0.8605   |
| 0.7211        | 2.0    | 74   | 0.2196          | 0.9070   |
| 0.5262        | 3.0    | 111  | 0.2471          | 0.9070   |
| 0.4001        | 4.0    | 148  | 0.2224          | 0.9147   |
| 0.5917        | 5.0    | 185  | 0.1857          | 0.9225   |
| 0.3629        | 5.8493 | 216  | 0.2577          | 0.8915   |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 3.6.0
- Tokenizers 0.21.0

invalidshop validshop