---
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-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-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: 0.7329
- Accuracy: 0.8206

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5364        | 0.98  | 23   | 0.8286          | 0.7257   |
| 0.4948        | 1.97  | 46   | 0.6373          | 0.7958   |
| 0.2036        | 2.99  | 70   | 0.5860          | 0.8234   |
| 0.1158        | 3.98  | 93   | 0.6284          | 0.8151   |
| 0.0656        | 4.96  | 116  | 0.6982          | 0.8129   |
| 0.0568        | 5.99  | 140  | 0.7678          | 0.8217   |
| 0.0332        | 6.97  | 163  | 0.7208          | 0.8206   |
| 0.0279        | 8.0   | 187  | 0.7053          | 0.8217   |
| 0.0169        | 8.98  | 210  | 0.7489          | 0.8256   |
| 0.0125        | 9.84  | 230  | 0.7329          | 0.8206   |


### Framework versions

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