---
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-MM_Classification_base
  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: 0.8770806658130602
---

<!-- 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-MM_Classification_base

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2998
- Accuracy: 0.8771

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.887         | 1.0   | 19   | 0.4012          | 0.8566   |
| 0.4302        | 2.0   | 38   | 0.3361          | 0.8656   |
| 0.3477        | 3.0   | 57   | 0.3272          | 0.8656   |
| 0.3281        | 4.0   | 76   | 0.3129          | 0.8694   |
| 0.308         | 5.0   | 95   | 0.2984          | 0.8732   |
| 0.2821        | 6.0   | 114  | 0.3010          | 0.8694   |
| 0.2763        | 7.0   | 133  | 0.2998          | 0.8771   |
| 0.2607        | 8.0   | 152  | 0.2938          | 0.8720   |
| 0.2502        | 9.0   | 171  | 0.2990          | 0.8732   |
| 0.2337        | 10.0  | 190  | 0.2978          | 0.8758   |


### Framework versions

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