---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-ve-U13-b-12
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5434782608695652
---

<!-- 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-ve-U13-b-12

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: 0.9160
- Accuracy: 0.5435

## 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: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 8    | 1.3788          | 0.4348   |
| 1.3828        | 2.0   | 16   | 1.3084          | 0.5      |
| 1.2902        | 3.0   | 24   | 1.1908          | 0.4783   |
| 1.1227        | 4.0   | 32   | 1.1055          | 0.4130   |
| 0.9806        | 5.0   | 40   | 1.0173          | 0.5217   |
| 0.9806        | 6.0   | 48   | 0.9396          | 0.5217   |
| 0.8629        | 7.0   | 56   | 0.9529          | 0.5      |
| 0.7707        | 8.0   | 64   | 0.9449          | 0.5217   |
| 0.7411        | 9.0   | 72   | 0.9160          | 0.5435   |
| 0.671         | 10.0  | 80   | 0.9073          | 0.5435   |
| 0.671         | 11.0  | 88   | 0.9192          | 0.5435   |
| 0.6501        | 12.0  | 96   | 0.9456          | 0.5      |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0