---
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: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8693982074263764
---

<!-- 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: 0.3468
- Accuracy: 0.8694

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0476        | 1.0   | 19   | 0.7707          | 0.6530   |
| 0.6226        | 2.0   | 38   | 0.4743          | 0.8105   |
| 0.4477        | 3.0   | 57   | 0.4133          | 0.8323   |
| 0.3963        | 4.0   | 76   | 0.3813          | 0.8476   |
| 0.3694        | 5.0   | 95   | 0.3753          | 0.8540   |
| 0.3451        | 6.0   | 114  | 0.3587          | 0.8489   |
| 0.3382        | 7.0   | 133  | 0.3531          | 0.8451   |
| 0.3253        | 8.0   | 152  | 0.3498          | 0.8579   |
| 0.3121        | 9.0   | 171  | 0.3437          | 0.8579   |
| 0.2855        | 10.0  | 190  | 0.3447          | 0.8656   |
| 0.2961        | 11.0  | 209  | 0.3350          | 0.8617   |
| 0.273         | 12.0  | 228  | 0.3484          | 0.8566   |
| 0.2745        | 13.0  | 247  | 0.3433          | 0.8604   |
| 0.2613        | 14.0  | 266  | 0.3498          | 0.8643   |
| 0.2527        | 15.0  | 285  | 0.3365          | 0.8579   |
| 0.2619        | 16.0  | 304  | 0.3450          | 0.8617   |
| 0.2436        | 17.0  | 323  | 0.3454          | 0.8681   |
| 0.2518        | 18.0  | 342  | 0.3437          | 0.8681   |
| 0.243         | 19.0  | 361  | 0.3468          | 0.8694   |
| 0.2415        | 20.0  | 380  | 0.3455          | 0.8694   |


### Framework versions

- Transformers 4.43.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1