---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: swin-tiny-patch4-window7-224-finetuned
  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

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9034
- Accuracy: 0.6660
- Precision: 0.6546
- Recall: 0.6660
- F1: 0.6519

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0809        | 0.9846 | 32   | 1.0485          | 0.5833   | 0.5506    | 0.5833 | 0.5627 |
| 1.0052        | 2.0    | 65   | 1.0600          | 0.5727   | 0.5941    | 0.5727 | 0.5170 |
| 0.9429        | 2.9846 | 97   | 0.9755          | 0.6160   | 0.5878    | 0.6160 | 0.5837 |
| 0.9497        | 4.0    | 130  | 0.9318          | 0.6497   | 0.6458    | 0.6497 | 0.6313 |
| 0.8807        | 4.9846 | 162  | 0.9541          | 0.6304   | 0.6321    | 0.6304 | 0.6200 |
| 0.8089        | 6.0    | 195  | 0.9556          | 0.6266   | 0.6270    | 0.6266 | 0.6150 |
| 0.801         | 6.9846 | 227  | 0.9050          | 0.6603   | 0.6512    | 0.6603 | 0.6472 |
| 0.7753        | 8.0    | 260  | 0.9134          | 0.6506   | 0.6440    | 0.6506 | 0.6440 |
| 0.6986        | 8.9846 | 292  | 0.9138          | 0.6554   | 0.6468    | 0.6554 | 0.6436 |
| 0.7107        | 9.8462 | 320  | 0.9034          | 0.6660   | 0.6546    | 0.6660 | 0.6519 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1