---
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-200k
  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: 0.8359511343804538
---

<!-- 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-200k

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: 0.3715
- Accuracy: 0.8360

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7044        | 0.93  | 10   | 0.6932          | 0.5410   |
| 0.6768        | 1.95  | 21   | 0.6407          | 0.6614   |
| 0.6359        | 2.98  | 32   | 0.5647          | 0.7208   |
| 0.5989        | 4.0   | 43   | 0.5674          | 0.7086   |
| 0.5831        | 4.93  | 53   | 0.5108          | 0.7679   |
| 0.549         | 5.95  | 64   | 0.4882          | 0.7836   |
| 0.5341        | 6.98  | 75   | 0.4831          | 0.7714   |
| 0.5172        | 8.0   | 86   | 0.4422          | 0.8115   |
| 0.4961        | 8.93  | 96   | 0.4422          | 0.7941   |
| 0.4796        | 9.95  | 107  | 0.4066          | 0.8098   |
| 0.4776        | 10.98 | 118  | 0.3906          | 0.8185   |
| 0.4668        | 12.0  | 129  | 0.4135          | 0.8150   |
| 0.4588        | 12.93 | 139  | 0.3884          | 0.8202   |
| 0.448         | 13.95 | 150  | 0.3764          | 0.8220   |
| 0.4508        | 14.98 | 161  | 0.3802          | 0.8220   |
| 0.43          | 16.0  | 172  | 0.3829          | 0.8150   |
| 0.4347        | 16.93 | 182  | 0.3857          | 0.8133   |
| 0.4232        | 17.95 | 193  | 0.3819          | 0.8150   |
| 0.4289        | 18.98 | 204  | 0.4055          | 0.8080   |
| 0.4271        | 20.0  | 215  | 0.3577          | 0.8377   |
| 0.4301        | 20.93 | 225  | 0.3598          | 0.8272   |
| 0.4257        | 21.95 | 236  | 0.3780          | 0.8237   |
| 0.4191        | 22.98 | 247  | 0.3545          | 0.8307   |
| 0.4164        | 24.0  | 258  | 0.4208          | 0.8115   |
| 0.4297        | 24.93 | 268  | 0.3817          | 0.8290   |
| 0.4168        | 25.95 | 279  | 0.3876          | 0.8220   |
| 0.4118        | 26.98 | 290  | 0.3670          | 0.8307   |
| 0.4042        | 28.0  | 301  | 0.3620          | 0.8290   |
| 0.4018        | 28.93 | 311  | 0.3670          | 0.8290   |
| 0.4074        | 29.95 | 322  | 0.3822          | 0.8290   |
| 0.4044        | 30.98 | 333  | 0.3561          | 0.8325   |
| 0.3998        | 32.0  | 344  | 0.3642          | 0.8377   |
| 0.3994        | 32.93 | 354  | 0.3721          | 0.8290   |
| 0.3982        | 33.95 | 365  | 0.3592          | 0.8394   |
| 0.4002        | 34.98 | 376  | 0.3740          | 0.8290   |
| 0.4014        | 36.0  | 387  | 0.3705          | 0.8325   |
| 0.3953        | 36.93 | 397  | 0.3865          | 0.8237   |
| 0.3934        | 37.95 | 408  | 0.3689          | 0.8342   |
| 0.3964        | 38.98 | 419  | 0.3570          | 0.8255   |
| 0.4027        | 40.0  | 430  | 0.3738          | 0.8325   |
| 0.392         | 40.93 | 440  | 0.3566          | 0.8342   |
| 0.3875        | 41.95 | 451  | 0.3652          | 0.8377   |
| 0.3866        | 42.98 | 462  | 0.3657          | 0.8342   |
| 0.396         | 44.0  | 473  | 0.3662          | 0.8342   |
| 0.3841        | 44.93 | 483  | 0.3764          | 0.8360   |
| 0.387         | 45.95 | 494  | 0.3687          | 0.8325   |
| 0.3844        | 46.51 | 500  | 0.3715          | 0.8360   |


### Framework versions

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