---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-in22k-finetuned_swinv1-all-classes-autotags-latest
  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: 0.9544554455445544
---

<!-- 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-base-patch4-window7-224-in22k-finetuned_swinv1-all-classes-autotags-latest

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1665
- Accuracy: 0.9545

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8729        | 1.0   | 63   | 0.6445          | 0.7921   |
| 0.4323        | 2.0   | 126  | 0.3358          | 0.8960   |
| 0.3421        | 3.0   | 189  | 0.2650          | 0.9178   |
| 0.198         | 4.0   | 252  | 0.2080          | 0.9327   |
| 0.1239        | 5.0   | 315  | 0.1797          | 0.9446   |
| 0.1053        | 6.0   | 378  | 0.1625          | 0.9525   |
| 0.1109        | 7.0   | 441  | 0.1712          | 0.9505   |
| 0.0411        | 8.0   | 504  | 0.1850          | 0.9436   |
| 0.0615        | 9.0   | 567  | 0.1695          | 0.9554   |
| 0.0407        | 10.0  | 630  | 0.1665          | 0.9545   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2