---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Train-Augmentation-V2-swinv2-base
  results: []
---

<!-- 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. -->

# Train-Augmentation-V2-swinv2-base

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9822
- Accuracy: 0.8459

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5894        | 0.99  | 109  | 0.7123          | 0.7481   |
| 0.2772        | 2.0   | 219  | 0.6394          | 0.7970   |
| 0.1863        | 3.0   | 329  | 0.7819          | 0.7669   |
| 0.0925        | 4.0   | 439  | 0.7062          | 0.8083   |
| 0.0461        | 4.99  | 548  | 0.8637          | 0.8120   |
| 0.0427        | 6.0   | 658  | 0.9080          | 0.7970   |
| 0.043         | 7.0   | 768  | 1.0747          | 0.8045   |
| 0.0074        | 8.0   | 878  | 0.9019          | 0.8421   |
| 0.0169        | 8.99  | 987  | 0.9099          | 0.8459   |
| 0.015         | 10.0  | 1097 | 0.9512          | 0.8647   |
| 0.0022        | 11.0  | 1207 | 1.0051          | 0.8609   |
| 0.0081        | 12.0  | 1317 | 1.0061          | 0.8308   |
| 0.0013        | 12.99 | 1426 | 0.9844          | 0.8534   |
| 0.0037        | 14.0  | 1536 | 0.9864          | 0.8459   |
| 0.0002        | 14.9  | 1635 | 0.9822          | 0.8459   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2