---
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-finetuned-PE
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8720186154741129
---

<!-- 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-finetuned-PE

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: 0.3083
- Accuracy: 0.8720

## 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: 0.00025
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 9    | 0.6391          | 0.6690   |
| 0.6873        | 1.95  | 19   | 0.5293          | 0.7376   |
| 0.6233        | 2.97  | 29   | 0.6385          | 0.6853   |
| 0.5976        | 4.0   | 39   | 0.4447          | 0.7970   |
| 0.5552        | 4.92  | 48   | 0.4029          | 0.8266   |
| 0.552         | 5.95  | 58   | 0.3675          | 0.8429   |
| 0.5055        | 6.97  | 68   | 0.3409          | 0.8581   |
| 0.4816        | 8.0   | 78   | 0.3322          | 0.8615   |
| 0.455         | 8.92  | 87   | 0.3166          | 0.8639   |
| 0.4428        | 9.95  | 97   | 0.3100          | 0.8662   |
| 0.4398        | 10.97 | 107  | 0.3713          | 0.8365   |
| 0.4318        | 12.0  | 117  | 0.4019          | 0.8284   |
| 0.4431        | 12.92 | 126  | 0.3074          | 0.8714   |
| 0.4437        | 13.95 | 136  | 0.3156          | 0.8656   |
| 0.4482        | 14.97 | 146  | 0.3516          | 0.8476   |
| 0.4353        | 16.0  | 156  | 0.3162          | 0.8598   |
| 0.4218        | 16.92 | 165  | 0.3018          | 0.8685   |
| 0.4111        | 17.95 | 175  | 0.3143          | 0.8650   |
| 0.4224        | 18.97 | 185  | 0.3146          | 0.8592   |
| 0.4114        | 20.0  | 195  | 0.3097          | 0.8691   |
| 0.4103        | 20.92 | 204  | 0.3038          | 0.8703   |
| 0.3989        | 21.95 | 214  | 0.2893          | 0.8796   |
| 0.3908        | 22.97 | 224  | 0.2956          | 0.8755   |
| 0.3923        | 24.0  | 234  | 0.3041          | 0.8685   |
| 0.3842        | 24.92 | 243  | 0.2876          | 0.8749   |
| 0.3808        | 25.95 | 253  | 0.2907          | 0.8767   |
| 0.382         | 26.97 | 263  | 0.3018          | 0.8738   |
| 0.3816        | 28.0  | 273  | 0.2812          | 0.8825   |
| 0.379         | 28.92 | 282  | 0.2960          | 0.8633   |
| 0.3858        | 29.95 | 292  | 0.2960          | 0.8743   |
| 0.3546        | 30.97 | 302  | 0.2850          | 0.8807   |
| 0.3656        | 32.0  | 312  | 0.2905          | 0.8784   |
| 0.3707        | 32.92 | 321  | 0.2926          | 0.8743   |
| 0.3651        | 33.95 | 331  | 0.2941          | 0.8796   |
| 0.3584        | 34.97 | 341  | 0.3133          | 0.8615   |
| 0.36          | 36.0  | 351  | 0.3181          | 0.8679   |
| 0.3496        | 36.92 | 360  | 0.3036          | 0.8685   |
| 0.3458        | 37.95 | 370  | 0.2939          | 0.8732   |
| 0.3431        | 38.97 | 380  | 0.3062          | 0.8703   |
| 0.3512        | 40.0  | 390  | 0.2914          | 0.8755   |
| 0.3512        | 40.92 | 399  | 0.3164          | 0.8674   |
| 0.3403        | 41.95 | 409  | 0.3063          | 0.8679   |
| 0.3423        | 42.97 | 419  | 0.3018          | 0.8720   |
| 0.3312        | 44.0  | 429  | 0.3094          | 0.8697   |
| 0.3365        | 44.92 | 438  | 0.3062          | 0.8755   |
| 0.3319        | 45.95 | 448  | 0.3081          | 0.8720   |
| 0.3409        | 46.15 | 450  | 0.3083          | 0.8720   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3