---
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-MM_Classification
  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: 0.8915401301518439
---

<!-- 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-MM_Classification

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: 0.2895
- Accuracy: 0.8915

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0635        | 0.9846 | 16   | 0.7524          | 0.6725   |
| 0.4571        | 1.9692 | 32   | 0.3692          | 0.8742   |
| 0.3819        | 2.9538 | 48   | 0.3500          | 0.8688   |
| 0.3278        | 4.0    | 65   | 0.3158          | 0.8796   |
| 0.2941        | 4.9846 | 81   | 0.2886          | 0.8883   |
| 0.2912        | 5.9692 | 97   | 0.2895          | 0.8915   |
| 0.2575        | 6.9538 | 113  | 0.2801          | 0.8839   |
| 0.2604        | 8.0    | 130  | 0.2847          | 0.8861   |
| 0.2519        | 8.9846 | 146  | 0.2804          | 0.8872   |
| 0.2592        | 9.8462 | 160  | 0.2795          | 0.8872   |


### Framework versions

- Transformers 4.43.2
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1