---
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_v3_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_v3_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: 1.9857
- Accuracy: 0.6785

## 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: 512
- eval_batch_size: 512
- 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 |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 1.6863        | 1.0   | 1313  | 0.5757   | 1.9559          |
| 1.3275        | 2.0   | 2626  | 0.6061   | 1.8276          |
| 1.151         | 3.0   | 3939  | 0.6130   | 1.8857          |
| 1.0336        | 4.0   | 5252  | 0.6322   | 1.8160          |
| 0.947         | 5.0   | 6565  | 0.6317   | 1.8051          |
| 0.8595        | 6.0   | 7878  | 0.6443   | 1.7996          |
| 0.801         | 7.0   | 9191  | 0.6534   | 1.7987          |
| 0.7508        | 8.0   | 10504 | 0.6522   | 1.7864          |
| 0.694         | 9.0   | 11817 | 0.6526   | 1.8871          |
| 0.6523        | 10.0  | 13130 | 0.6648   | 1.8057          |
| 0.5976        | 11.0  | 14443 | 0.6707   | 1.8514          |
| 0.5743        | 12.0  | 15756 | 0.6629   | 1.9271          |
| 0.5426        | 13.0  | 17069 | 0.6692   | 1.9221          |
| 0.5092        | 14.0  | 18382 | 0.6752   | 1.9164          |
| 0.4808        | 15.0  | 19695 | 0.6743   | 1.9259          |
| 0.4611        | 16.0  | 21008 | 0.6785   | 1.9857          |


### Framework versions

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