---
library_name: transformers
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-RD-da-colab
  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: 0.5036363636363637
---

<!-- 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. -->

# swinv2-tiny-patch4-window8-256-RD-da-colab

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: 10.2420
- Accuracy: 0.5036

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1347        | 1.0   | 96   | 10.0386         | 0.4982   |
| 0.1556        | 2.0   | 192  | 9.5018          | 0.5      |
| 0.1051        | 3.0   | 288  | 9.9516          | 0.4982   |
| 0.1154        | 4.0   | 384  | 10.8351         | 0.4945   |
| 0.0909        | 5.0   | 480  | 11.6091         | 0.4945   |
| 0.0923        | 6.0   | 576  | 9.0530          | 0.5      |
| 0.1089        | 7.0   | 672  | 11.6765         | 0.4927   |
| 0.0959        | 8.0   | 768  | 11.5132         | 0.4982   |
| 0.1266        | 9.0   | 864  | 10.2420         | 0.5036   |
| 0.106         | 10.0  | 960  | 11.1262         | 0.4945   |
| 0.0831        | 11.0  | 1056 | 11.5815         | 0.4964   |
| 0.0819        | 12.0  | 1152 | 11.6394         | 0.4964   |
| 0.0862        | 13.0  | 1248 | 10.9660         | 0.4982   |
| 0.0754        | 14.0  | 1344 | 9.5463          | 0.4982   |
| 0.06          | 15.0  | 1440 | 10.2678         | 0.4964   |
| 0.0828        | 16.0  | 1536 | 11.4973         | 0.4927   |
| 0.0675        | 17.0  | 1632 | 10.5019         | 0.4964   |
| 0.0687        | 18.0  | 1728 | 10.6483         | 0.4982   |
| 0.0548        | 19.0  | 1824 | 11.2166         | 0.4964   |
| 0.0658        | 20.0  | 1920 | 11.5459         | 0.4945   |
| 0.0565        | 21.0  | 2016 | 11.5899         | 0.4945   |
| 0.0807        | 22.0  | 2112 | 10.7066         | 0.5      |
| 0.0289        | 23.0  | 2208 | 10.6253         | 0.4982   |
| 0.0755        | 24.0  | 2304 | 10.4856         | 0.5018   |
| 0.0483        | 25.0  | 2400 | 11.3838         | 0.4964   |
| 0.0732        | 26.0  | 2496 | 11.1971         | 0.4927   |
| 0.1424        | 27.0  | 2592 | 11.4581         | 0.4945   |
| 0.0814        | 28.0  | 2688 | 11.3341         | 0.4945   |
| 0.101         | 29.0  | 2784 | 11.5705         | 0.4927   |
| 0.0894        | 30.0  | 2880 | 11.5259         | 0.4927   |
| 0.0707        | 31.0  | 2976 | 11.1753         | 0.4945   |
| 0.1289        | 32.0  | 3072 | 10.5668         | 0.4964   |
| 0.0991        | 33.0  | 3168 | 11.1013         | 0.4945   |
| 0.0615        | 34.0  | 3264 | 11.0973         | 0.4945   |
| 0.0784        | 35.0  | 3360 | 11.0716         | 0.4945   |
| 0.0792        | 36.0  | 3456 | 11.0241         | 0.4945   |
| 0.1032        | 37.0  | 3552 | 11.2338         | 0.4945   |
| 0.0837        | 38.0  | 3648 | 11.4256         | 0.4927   |
| 0.0722        | 39.0  | 3744 | 11.3971         | 0.4945   |
| 0.079         | 40.0  | 3840 | 11.3523         | 0.4945   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3