---
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-ve-U13-b-80b
  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: 0.7391304347826086
---

<!-- 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-ve-U13-b-80b

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: 0.7057
- Accuracy: 0.7391

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.3861          | 0.1304   |
| 1.386         | 2.0   | 13   | 1.3837          | 0.4348   |
| 1.386         | 2.92  | 19   | 1.3776          | 0.3043   |
| 1.3807        | 4.0   | 26   | 1.3570          | 0.2391   |
| 1.3386        | 4.92  | 32   | 1.3224          | 0.2174   |
| 1.3386        | 6.0   | 39   | 1.2085          | 0.3478   |
| 1.209         | 6.92  | 45   | 1.1056          | 0.4565   |
| 1.0561        | 8.0   | 52   | 1.0507          | 0.4783   |
| 1.0561        | 8.92  | 58   | 1.0161          | 0.4565   |
| 0.9157        | 10.0  | 65   | 0.8613          | 0.6304   |
| 0.8002        | 10.92 | 71   | 0.9073          | 0.5652   |
| 0.8002        | 12.0  | 78   | 0.8300          | 0.6304   |
| 0.7181        | 12.92 | 84   | 0.8958          | 0.5870   |
| 0.6405        | 14.0  | 91   | 0.8075          | 0.7174   |
| 0.6405        | 14.92 | 97   | 0.7478          | 0.6957   |
| 0.6064        | 16.0  | 104  | 0.7370          | 0.7174   |
| 0.5556        | 16.92 | 110  | 0.7057          | 0.7391   |
| 0.5556        | 18.0  | 117  | 0.7395          | 0.6522   |
| 0.4822        | 18.92 | 123  | 0.8734          | 0.6957   |
| 0.4241        | 20.0  | 130  | 0.9991          | 0.6739   |
| 0.4241        | 20.92 | 136  | 0.8416          | 0.7174   |
| 0.4307        | 22.0  | 143  | 0.9195          | 0.6957   |
| 0.4307        | 22.92 | 149  | 0.9211          | 0.6522   |
| 0.381         | 24.0  | 156  | 0.9683          | 0.6087   |
| 0.3707        | 24.92 | 162  | 1.0067          | 0.6739   |
| 0.3707        | 26.0  | 169  | 0.9793          | 0.6522   |
| 0.3918        | 26.92 | 175  | 0.9758          | 0.6739   |
| 0.3513        | 28.0  | 182  | 0.9761          | 0.6739   |
| 0.3513        | 28.92 | 188  | 1.0745          | 0.6304   |
| 0.2739        | 30.0  | 195  | 1.0775          | 0.6739   |
| 0.2882        | 30.92 | 201  | 1.1521          | 0.6739   |
| 0.2882        | 32.0  | 208  | 1.2072          | 0.6522   |
| 0.2588        | 32.92 | 214  | 1.1374          | 0.6739   |
| 0.2498        | 34.0  | 221  | 1.2131          | 0.6522   |
| 0.2498        | 34.92 | 227  | 1.1309          | 0.7391   |
| 0.2584        | 36.0  | 234  | 1.2828          | 0.6957   |
| 0.2228        | 36.92 | 240  | 1.1381          | 0.6739   |
| 0.2228        | 38.0  | 247  | 1.2116          | 0.6522   |
| 0.2408        | 38.92 | 253  | 1.1962          | 0.6739   |
| 0.2042        | 40.0  | 260  | 1.2557          | 0.6739   |
| 0.2042        | 40.92 | 266  | 1.3511          | 0.6739   |
| 0.2141        | 42.0  | 273  | 1.3636          | 0.6304   |
| 0.2141        | 42.92 | 279  | 1.3084          | 0.6304   |
| 0.2135        | 44.0  | 286  | 1.3847          | 0.6087   |
| 0.191         | 44.92 | 292  | 1.2408          | 0.6957   |
| 0.191         | 46.0  | 299  | 1.1750          | 0.7174   |
| 0.1833        | 46.92 | 305  | 1.1804          | 0.6957   |
| 0.189         | 48.0  | 312  | 1.1867          | 0.7174   |
| 0.189         | 48.92 | 318  | 1.0623          | 0.7391   |
| 0.2196        | 50.0  | 325  | 1.2626          | 0.6957   |
| 0.1505        | 50.92 | 331  | 1.2745          | 0.6957   |
| 0.1505        | 52.0  | 338  | 1.3473          | 0.6957   |
| 0.1604        | 52.92 | 344  | 1.3535          | 0.6522   |
| 0.1377        | 54.0  | 351  | 1.3873          | 0.6522   |
| 0.1377        | 54.92 | 357  | 1.4287          | 0.6522   |
| 0.1752        | 56.0  | 364  | 1.3014          | 0.6957   |
| 0.1684        | 56.92 | 370  | 1.3564          | 0.6739   |
| 0.1684        | 58.0  | 377  | 1.4165          | 0.6957   |
| 0.1597        | 58.92 | 383  | 1.3624          | 0.6739   |
| 0.1393        | 60.0  | 390  | 1.3018          | 0.6957   |
| 0.1393        | 60.92 | 396  | 1.3197          | 0.6739   |
| 0.1347        | 62.0  | 403  | 1.3542          | 0.6739   |
| 0.1347        | 62.92 | 409  | 1.3460          | 0.6739   |
| 0.155         | 64.0  | 416  | 1.3998          | 0.6739   |
| 0.1198        | 64.92 | 422  | 1.3982          | 0.6739   |
| 0.1198        | 66.0  | 429  | 1.3989          | 0.6522   |
| 0.1318        | 66.92 | 435  | 1.4035          | 0.6522   |
| 0.1382        | 68.0  | 442  | 1.3626          | 0.6522   |
| 0.1382        | 68.92 | 448  | 1.3714          | 0.6522   |
| 0.1451        | 70.0  | 455  | 1.4174          | 0.6739   |
| 0.1203        | 70.92 | 461  | 1.4343          | 0.6739   |
| 0.1203        | 72.0  | 468  | 1.4045          | 0.6522   |
| 0.141         | 72.92 | 474  | 1.3904          | 0.6522   |
| 0.1516        | 73.85 | 480  | 1.3849          | 0.6522   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0