---
library_name: transformers
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-finetuned-noh
  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-finetuned-noh

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: 0.4349
- Accuracy: 0.8621

## 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: 4
- total_train_batch_size: 64
- 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5322        | 1.0    | 23   | 0.4647          | 0.7619   |
| 0.4535        | 2.0    | 46   | 0.4359          | 0.8194   |
| 0.3854        | 3.0    | 69   | 0.3514          | 0.8539   |
| 0.302         | 4.0    | 92   | 0.4349          | 0.8621   |
| 0.2571        | 5.0    | 115  | 0.5112          | 0.8095   |
| 0.2104        | 6.0    | 138  | 0.4453          | 0.8259   |
| 0.1702        | 7.0    | 161  | 0.5550          | 0.7833   |
| 0.1682        | 8.0    | 184  | 0.5313          | 0.7947   |
| 0.136         | 9.0    | 207  | 0.5452          | 0.8276   |
| 0.1415        | 9.5778 | 220  | 0.5352          | 0.8210   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1
- Datasets 2.19.1
- Tokenizers 0.21.0