---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: 2025-01-21-15-57-43-swin-base-patch4-window7-224
  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. -->

# 2025-01-21-15-57-43-swin-base-patch4-window7-224

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0384
- Precision: 0.9928
- Recall: 0.9926
- F1: 0.9926
- Accuracy: 0.992
- Top1 Accuracy: 0.9926
- Error Rate: 0.0080

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 3407
- 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 | Precision | Recall | F1     | Accuracy | Top1 Accuracy | Error Rate |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
| 0.732         | 1.0   | 34   | 0.3980          | 0.9165    | 0.8741 | 0.8590 | 0.8649   | 0.8741        | 0.1351     |
| 0.2462        | 2.0   | 68   | 0.1051          | 0.9538    | 0.9481 | 0.9484 | 0.9499   | 0.9481        | 0.0501     |
| 0.1991        | 3.0   | 102  | 0.0384          | 0.9928    | 0.9926 | 0.9926 | 0.992    | 0.9926        | 0.0080     |
| 0.1559        | 4.0   | 136  | 0.0890          | 0.9802    | 0.9778 | 0.9780 | 0.9777   | 0.9778        | 0.0223     |
| 0.1024        | 5.0   | 170  | 0.1092          | 0.9863    | 0.9852 | 0.9852 | 0.9846   | 0.9852        | 0.0154     |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3