
<!-- 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. -->

# convnextv2-tiny-22k-384-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4641
- Accuracy: 0.8675
- Precision: 0.8664
- Recall: 0.8675
- F1: 0.8661

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.5875        | 0.99  | 62   | 1.3967          | 0.5423   | 0.5237    | 0.5423 | 0.5001 |
| 0.8561        | 2.0   | 125  | 0.7084          | 0.7773   | 0.7769    | 0.7773 | 0.7692 |
| 0.7139        | 2.99  | 187  | 0.5607          | 0.8230   | 0.8201    | 0.8230 | 0.8148 |
| 0.5799        | 4.0   | 250  | 0.4982          | 0.8410   | 0.8428    | 0.8410 | 0.8324 |
| 0.5352        | 4.99  | 312  | 0.4781          | 0.8461   | 0.8470    | 0.8461 | 0.8446 |
| 0.539         | 6.0   | 375  | 0.4538          | 0.8523   | 0.8578    | 0.8523 | 0.8482 |
| 0.5129        | 6.99  | 437  | 0.4496          | 0.8472   | 0.8486    | 0.8472 | 0.8468 |
| 0.4685        | 8.0   | 500  | 0.4458          | 0.8551   | 0.8589    | 0.8551 | 0.8542 |
| 0.4675        | 8.99  | 562  | 0.4352          | 0.8613   | 0.8651    | 0.8613 | 0.8579 |
| 0.441         | 10.0  | 625  | 0.4076          | 0.8636   | 0.8616    | 0.8636 | 0.8607 |
| 0.4214        | 10.99 | 687  | 0.4346          | 0.8517   | 0.8556    | 0.8517 | 0.8522 |
| 0.4016        | 12.0  | 750  | 0.4300          | 0.8591   | 0.8597    | 0.8591 | 0.8573 |
| 0.3913        | 12.99 | 812  | 0.4164          | 0.8625   | 0.8624    | 0.8625 | 0.8601 |
| 0.3882        | 14.0  | 875  | 0.4246          | 0.8591   | 0.8618    | 0.8591 | 0.8570 |
| 0.3341        | 14.99 | 937  | 0.4321          | 0.8574   | 0.8555    | 0.8574 | 0.8555 |
| 0.3522        | 16.0  | 1000 | 0.4322          | 0.8568   | 0.8561    | 0.8568 | 0.8542 |
| 0.2824        | 16.99 | 1062 | 0.4364          | 0.8608   | 0.8606    | 0.8608 | 0.8586 |
| 0.315         | 18.0  | 1125 | 0.4495          | 0.8579   | 0.8581    | 0.8579 | 0.8559 |
| 0.3084        | 18.99 | 1187 | 0.4536          | 0.8608   | 0.8593    | 0.8608 | 0.8590 |
| 0.2864        | 20.0  | 1250 | 0.4417          | 0.8630   | 0.8621    | 0.8630 | 0.8607 |
| 0.2654        | 20.99 | 1312 | 0.4585          | 0.8630   | 0.8628    | 0.8630 | 0.8610 |
| 0.3067        | 22.0  | 1375 | 0.4673          | 0.8557   | 0.8562    | 0.8557 | 0.8538 |
| 0.2771        | 22.99 | 1437 | 0.4679          | 0.8596   | 0.8577    | 0.8596 | 0.8577 |
| 0.2588        | 24.0  | 1500 | 0.4616          | 0.8653   | 0.8646    | 0.8653 | 0.8633 |
| 0.2583        | 24.99 | 1562 | 0.4726          | 0.8591   | 0.8572    | 0.8591 | 0.8567 |
| 0.2517        | 26.0  | 1625 | 0.4618          | 0.8630   | 0.8625    | 0.8630 | 0.8619 |
| 0.2454        | 26.99 | 1687 | 0.4612          | 0.8641   | 0.8630    | 0.8641 | 0.8629 |
| 0.259         | 28.0  | 1750 | 0.4685          | 0.8613   | 0.8595    | 0.8613 | 0.8594 |
| 0.2388        | 28.99 | 1812 | 0.4668          | 0.8636   | 0.8622    | 0.8636 | 0.8620 |
| 0.2414        | 29.76 | 1860 | 0.4641          | 0.8675   | 0.8664    | 0.8675 | 0.8661 |


### Framework versions

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

disturbed galaxies merging galaxies round smooth galaxies in-between round smooth galaxies cigar shaped smooth galaxies barred spiral galaxies unbarred tight spiral galaxies unbarred loose spiral galaxies edge-on galaxies without bulge edge-on galaxies with bulge