---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-tiny-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-tiny-patch4-window8-256-finetuned-galaxy10-decals

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4357
- Accuracy: 0.8585

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.318         | 0.9940  | 124  | 1.0409          | 0.6359   |
| 0.9268        | 1.9960  | 249  | 0.7164          | 0.7497   |
| 0.8221        | 2.9980  | 374  | 0.6210          | 0.7875   |
| 0.7276        | 4.0     | 499  | 0.5564          | 0.8162   |
| 0.6425        | 4.9940  | 623  | 0.5226          | 0.8162   |
| 0.6518        | 5.9960  | 748  | 0.5377          | 0.8185   |
| 0.6096        | 6.9980  | 873  | 0.5341          | 0.8219   |
| 0.6282        | 8.0     | 998  | 0.4718          | 0.8399   |
| 0.5394        | 8.9940  | 1122 | 0.5113          | 0.8281   |
| 0.5718        | 9.9960  | 1247 | 0.5019          | 0.8292   |
| 0.5507        | 10.9980 | 1372 | 0.4545          | 0.8461   |
| 0.4921        | 12.0    | 1497 | 0.4613          | 0.8416   |
| 0.5571        | 12.9940 | 1621 | 0.4587          | 0.8416   |
| 0.512         | 13.9960 | 1746 | 0.4673          | 0.8512   |
| 0.4855        | 14.9980 | 1871 | 0.4641          | 0.8489   |
| 0.4895        | 16.0    | 1996 | 0.4556          | 0.8450   |
| 0.4809        | 16.9940 | 2120 | 0.4317          | 0.8523   |
| 0.4785        | 17.9960 | 2245 | 0.4338          | 0.8534   |
| 0.444         | 18.9980 | 2370 | 0.4357          | 0.8579   |
| 0.4255        | 19.8798 | 2480 | 0.4357          | 0.8585   |


### Framework versions

- Transformers 4.40.1
- Pytorch 1.12.1+cu116
- Datasets 2.19.0
- Tokenizers 0.19.1