---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window8-256
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: swinv2-base-patch4-window8-256-finetuned-galaxy10-decals
  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. -->

# swinv2-base-patch4-window8-256-finetuned-galaxy10-decals

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4829
- Accuracy: 0.8540
- Precision: 0.8529
- Recall: 0.8540
- F1: 0.8520

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6195        | 0.99  | 62   | 1.4006          | 0.5101   | 0.4910    | 0.5101 | 0.4782 |
| 0.9423        | 2.0   | 125  | 0.7209          | 0.7616   | 0.7617    | 0.7616 | 0.7531 |
| 0.8171        | 2.99  | 187  | 0.5842          | 0.8010   | 0.7950    | 0.8010 | 0.7938 |
| 0.6609        | 4.0   | 250  | 0.5000          | 0.8224   | 0.8159    | 0.8224 | 0.8143 |
| 0.5927        | 4.99  | 312  | 0.5367          | 0.8191   | 0.8211    | 0.8191 | 0.8184 |
| 0.624         | 6.0   | 375  | 0.4946          | 0.8286   | 0.8295    | 0.8286 | 0.8212 |
| 0.5891        | 6.99  | 437  | 0.5068          | 0.8219   | 0.8244    | 0.8219 | 0.8201 |
| 0.5597        | 8.0   | 500  | 0.5071          | 0.8230   | 0.8382    | 0.8230 | 0.8198 |
| 0.5292        | 8.99  | 562  | 0.4464          | 0.8444   | 0.8462    | 0.8444 | 0.8426 |
| 0.5143        | 10.0  | 625  | 0.4556          | 0.8371   | 0.8420    | 0.8371 | 0.8350 |
| 0.5122        | 10.99 | 687  | 0.4765          | 0.8382   | 0.8433    | 0.8382 | 0.8369 |
| 0.4647        | 12.0  | 750  | 0.4900          | 0.8365   | 0.8443    | 0.8365 | 0.8348 |
| 0.4769        | 12.99 | 812  | 0.4639          | 0.8427   | 0.8475    | 0.8427 | 0.8396 |
| 0.4804        | 14.0  | 875  | 0.4468          | 0.8484   | 0.8499    | 0.8484 | 0.8461 |
| 0.4452        | 14.99 | 937  | 0.4492          | 0.8512   | 0.8522    | 0.8512 | 0.8505 |
| 0.4283        | 16.0  | 1000 | 0.4660          | 0.8433   | 0.8446    | 0.8433 | 0.8401 |
| 0.3788        | 16.99 | 1062 | 0.4689          | 0.8478   | 0.8454    | 0.8478 | 0.8444 |
| 0.41          | 18.0  | 1125 | 0.4543          | 0.8506   | 0.8502    | 0.8506 | 0.8480 |
| 0.4007        | 18.99 | 1187 | 0.4766          | 0.8478   | 0.8511    | 0.8478 | 0.8455 |
| 0.406         | 20.0  | 1250 | 0.4716          | 0.8478   | 0.8474    | 0.8478 | 0.8444 |
| 0.3777        | 20.99 | 1312 | 0.5026          | 0.8455   | 0.8454    | 0.8455 | 0.8430 |
| 0.3972        | 22.0  | 1375 | 0.5108          | 0.8393   | 0.8402    | 0.8393 | 0.8371 |
| 0.3665        | 22.99 | 1437 | 0.4934          | 0.8489   | 0.8498    | 0.8489 | 0.8474 |
| 0.3569        | 24.0  | 1500 | 0.4989          | 0.8495   | 0.8495    | 0.8495 | 0.8478 |
| 0.3735        | 24.99 | 1562 | 0.4918          | 0.8495   | 0.8468    | 0.8495 | 0.8468 |
| 0.3301        | 26.0  | 1625 | 0.4927          | 0.8512   | 0.8512    | 0.8512 | 0.8488 |
| 0.3438        | 26.99 | 1687 | 0.4829          | 0.8540   | 0.8529    | 0.8540 | 0.8520 |
| 0.3553        | 28.0  | 1750 | 0.4935          | 0.8540   | 0.8530    | 0.8540 | 0.8512 |
| 0.3312        | 28.99 | 1812 | 0.4882          | 0.8517   | 0.8509    | 0.8517 | 0.8491 |
| 0.3319        | 29.76 | 1860 | 0.4876          | 0.8517   | 0.8516    | 0.8517 | 0.8497 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1