---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SWIN_finetuned_frozen_v5_cont
  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. -->

# SWIN_finetuned_frozen_v5_cont

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1793
- Accuracy: 0.7000

## 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: 0.0004
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15.0

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.6306        | 1.0   | 2625  | 0.6565   | 1.9169          |
| 0.5977        | 2.0   | 5250  | 0.6614   | 1.9120          |
| 0.5472        | 3.0   | 7875  | 0.6635   | 1.9410          |
| 0.513         | 4.0   | 10500 | 0.6679   | 1.9818          |
| 0.4714        | 5.0   | 13125 | 0.6711   | 1.9428          |
| 0.4378        | 6.0   | 15750 | 0.6727   | 2.0051          |
| 0.4105        | 7.0   | 18375 | 0.6778   | 1.9917          |
| 0.3837        | 8.0   | 21000 | 0.6792   | 2.0413          |
| 0.3602        | 9.0   | 23625 | 0.6870   | 2.0738          |
| 0.336         | 10.0  | 26250 | 2.0872   | 0.6876          |
| 0.3057        | 11.0  | 28875 | 2.1163   | 0.6894          |
| 0.2856        | 12.0  | 31500 | 2.1105   | 0.6936          |
| 0.2704        | 13.0  | 34125 | 2.1685   | 0.6965          |
| 0.2503        | 14.0  | 36750 | 2.1627   | 0.6994          |
| 0.2362        | 15.0  | 39375 | 2.1793   | 0.7000          |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3