---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: swin-tiny-patch4-window7-224-image-classifier
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.748792270531401
    - name: F1
      type: f1
      value: 0.655421686746988
    - name: Precision
      type: precision
      value: 0.6267281105990783
    - name: Recall
      type: recall
      value: 0.6868686868686869
---

<!-- 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-image-classifier

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4362
- Accuracy: 0.7488
- F1: 0.6554
- Precision: 0.6267
- Recall: 0.6869

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5982        | 1.0   | 143  | 0.5693          | 0.6711   | 0.4144 | 0.5441    | 0.3346 |
| 0.4391        | 2.0   | 286  | 0.4924          | 0.7295   | 0.4849 | 0.7178    | 0.3662 |
| 0.3658        | 3.0   | 429  | 0.4332          | 0.7501   | 0.6459 | 0.6368    | 0.6553 |
| 0.3404        | 4.0   | 572  | 0.4202          | 0.7694   | 0.6525 | 0.6857    | 0.6225 |
| 0.3188        | 5.0   | 715  | 0.4362          | 0.7488   | 0.6554 | 0.6267    | 0.6869 |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1