---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Balanced-No-Augmentation-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. -->

# Balanced-No-Augmentation-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: 3.6109
- Accuracy: 0.5692

## 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: 16
- total_train_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2985        | 0.98  | 11   | 1.4531          | 0.4822   |
| 0.9081        | 1.97  | 22   | 1.5086          | 0.5731   |
| 0.4604        | 2.95  | 33   | 1.9810          | 0.5692   |
| 0.2255        | 3.93  | 44   | 3.0618          | 0.5415   |
| 0.1339        | 4.92  | 55   | 2.8634          | 0.5613   |
| 0.0883        | 5.99  | 67   | 3.0244          | 0.5652   |
| 0.0605        | 6.97  | 78   | 3.5175          | 0.5573   |
| 0.0506        | 7.96  | 89   | 3.4068          | 0.5850   |
| 0.0272        | 8.94  | 100  | 3.6996          | 0.5573   |
| 0.0262        | 9.83  | 110  | 3.6109          | 0.5692   |


### Framework versions

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