---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-classification
  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. -->

# swin-tiny-patch4-window7-224-classification

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2780
- Accuracy: 0.9264

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1469        | 1.0   | 100  | 0.3027          | 0.9127   |
| 0.1677        | 2.0   | 200  | 0.3351          | 0.9001   |
| 0.167         | 2.99  | 300  | 0.3875          | 0.8931   |
| 0.1556        | 4.0   | 401  | 0.3814          | 0.8969   |
| 0.1328        | 5.0   | 501  | 0.3281          | 0.9046   |
| 0.1           | 6.0   | 601  | 0.3726          | 0.9004   |
| 0.1188        | 6.99  | 701  | 0.3736          | 0.9046   |
| 0.1257        | 8.0   | 802  | 0.3381          | 0.9102   |
| 0.1017        | 9.0   | 902  | 0.2872          | 0.9215   |
| 0.0987        | 10.0  | 1002 | 0.3067          | 0.9176   |
| 0.0874        | 10.99 | 1102 | 0.2919          | 0.9165   |
| 0.0901        | 12.0  | 1203 | 0.2942          | 0.9229   |
| 0.0831        | 13.0  | 1303 | 0.2974          | 0.9232   |
| 0.0838        | 14.0  | 1403 | 0.2787          | 0.9264   |
| 0.0603        | 14.96 | 1500 | 0.2780          | 0.9264   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2