---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: msi-swinv2-tiny
  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: 0.6273762929829466
---

<!-- 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. -->

# msi-swinv2-tiny

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5764
- Accuracy: 0.6274

## 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: 1e-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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4392        | 1.0   | 2015  | 0.7935          | 0.6100   |
| 0.3266        | 2.0   | 4031  | 0.9694          | 0.6132   |
| 0.2673        | 3.0   | 6047  | 1.2037          | 0.6114   |
| 0.2222        | 4.0   | 8063  | 1.3734          | 0.6097   |
| 0.1922        | 5.0   | 10078 | 1.3308          | 0.6235   |
| 0.1716        | 6.0   | 12094 | 1.4758          | 0.6136   |
| 0.1742        | 7.0   | 14110 | 1.4332          | 0.6274   |
| 0.1653        | 8.0   | 16126 | 1.4940          | 0.6247   |
| 0.1429        | 9.0   | 18141 | 1.6058          | 0.6236   |
| 0.1546        | 10.0  | 20150 | 1.5764          | 0.6274   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0