---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Train-Test-Augmentation-NO-UPNormal-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-Test-Augmentation-NO-UPNormal-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: 0.5452
- Accuracy: 0.9030

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4905        | 1.0   | 86   | 0.5127          | 0.8252   |
| 0.2148        | 2.0   | 172  | 0.5452          | 0.8445   |
| 0.1355        | 3.0   | 258  | 0.5205          | 0.8608   |
| 0.0472        | 4.0   | 344  | 0.4481          | 0.8921   |
| 0.0229        | 5.0   | 430  | 0.5671          | 0.8782   |
| 0.0505        | 6.0   | 516  | 0.6136          | 0.8837   |
| 0.0254        | 7.0   | 602  | 0.6037          | 0.8891   |
| 0.0009        | 8.0   | 688  | 0.6371          | 0.8819   |
| 0.0034        | 9.0   | 774  | 0.5569          | 0.8981   |
| 0.0019        | 10.0  | 860  | 0.5452          | 0.9030   |


### Framework versions

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