---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window16-256
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: swinv2-tiny-patch4-window16-256-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-window16-256-finetuned-galaxy10-decals

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window16-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window16-256) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4595
- Accuracy: 0.8551
- Precision: 0.8536
- Recall: 0.8551
- F1: 0.8518

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.723         | 0.99  | 62   | 1.4631          | 0.4803   | 0.5152    | 0.4803 | 0.4359 |
| 1.1597        | 2.0   | 125  | 0.9498          | 0.6759   | 0.6942    | 0.6759 | 0.6657 |
| 0.9305        | 2.99  | 187  | 0.6600          | 0.7728   | 0.7592    | 0.7728 | 0.7620 |
| 0.7634        | 4.0   | 250  | 0.6276          | 0.7875   | 0.7831    | 0.7875 | 0.7765 |
| 0.6924        | 4.99  | 312  | 0.5762          | 0.7943   | 0.7972    | 0.7943 | 0.7934 |
| 0.6992        | 6.0   | 375  | 0.5421          | 0.8123   | 0.8128    | 0.8123 | 0.8059 |
| 0.6731        | 6.99  | 437  | 0.5244          | 0.8129   | 0.8153    | 0.8129 | 0.8108 |
| 0.6274        | 8.0   | 500  | 0.5279          | 0.8055   | 0.8140    | 0.8055 | 0.8019 |
| 0.6096        | 8.99  | 562  | 0.4737          | 0.8354   | 0.8336    | 0.8354 | 0.8321 |
| 0.5906        | 10.0  | 625  | 0.4792          | 0.8382   | 0.8382    | 0.8382 | 0.8357 |
| 0.5839        | 10.99 | 687  | 0.5093          | 0.8224   | 0.8322    | 0.8224 | 0.8199 |
| 0.5478        | 12.0  | 750  | 0.4601          | 0.8433   | 0.8429    | 0.8433 | 0.8411 |
| 0.5678        | 12.99 | 812  | 0.5018          | 0.8269   | 0.8322    | 0.8269 | 0.8233 |
| 0.5586        | 14.0  | 875  | 0.4503          | 0.8439   | 0.8444    | 0.8439 | 0.8423 |
| 0.5267        | 14.99 | 937  | 0.4492          | 0.8444   | 0.8416    | 0.8444 | 0.8424 |
| 0.5143        | 16.0  | 1000 | 0.4543          | 0.8484   | 0.8458    | 0.8484 | 0.8442 |
| 0.4608        | 16.99 | 1062 | 0.4616          | 0.8427   | 0.8419    | 0.8427 | 0.8398 |
| 0.4914        | 18.0  | 1125 | 0.4477          | 0.8501   | 0.8501    | 0.8501 | 0.8479 |
| 0.4889        | 18.99 | 1187 | 0.4738          | 0.8337   | 0.8383    | 0.8337 | 0.8310 |
| 0.4943        | 20.0  | 1250 | 0.4758          | 0.8388   | 0.8373    | 0.8388 | 0.8352 |
| 0.4759        | 20.99 | 1312 | 0.4550          | 0.8478   | 0.8484    | 0.8478 | 0.8456 |
| 0.49          | 22.0  | 1375 | 0.4529          | 0.8512   | 0.8520    | 0.8512 | 0.8489 |
| 0.4546        | 22.99 | 1437 | 0.4567          | 0.8472   | 0.8456    | 0.8472 | 0.8447 |
| 0.4638        | 24.0  | 1500 | 0.4598          | 0.8450   | 0.8438    | 0.8450 | 0.8431 |
| 0.4591        | 24.99 | 1562 | 0.4655          | 0.8529   | 0.8539    | 0.8529 | 0.8507 |
| 0.413         | 26.0  | 1625 | 0.4512          | 0.8546   | 0.8526    | 0.8546 | 0.8514 |
| 0.4268        | 26.99 | 1687 | 0.4511          | 0.8517   | 0.8506    | 0.8517 | 0.8496 |
| 0.4497        | 28.0  | 1750 | 0.4595          | 0.8551   | 0.8536    | 0.8551 | 0.8518 |
| 0.4183        | 28.99 | 1812 | 0.4556          | 0.8540   | 0.8532    | 0.8540 | 0.8512 |
| 0.4211        | 29.76 | 1860 | 0.4567          | 0.8529   | 0.8523    | 0.8529 | 0.8503 |


### Framework versions

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