---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: convnextv2-tiny-1k-224-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. -->

# convnextv2-tiny-1k-224-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3993
- Accuracy: 0.8732
- Precision: 0.8714
- Recall: 0.8732
- F1: 0.8715

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.8139        | 0.99  | 62   | 1.6803          | 0.4628   | 0.4589    | 0.4628 | 0.3836 |
| 1.0894        | 2.0   | 125  | 0.9304          | 0.6984   | 0.6965    | 0.6984 | 0.6800 |
| 0.8423        | 2.99  | 187  | 0.6630          | 0.7880   | 0.7858    | 0.7880 | 0.7826 |
| 0.6564        | 4.0   | 250  | 0.5769          | 0.8055   | 0.8091    | 0.8055 | 0.7970 |
| 0.5927        | 4.99  | 312  | 0.5283          | 0.8241   | 0.8276    | 0.8241 | 0.8240 |
| 0.5853        | 6.0   | 375  | 0.5106          | 0.8303   | 0.8342    | 0.8303 | 0.8237 |
| 0.5757        | 6.99  | 437  | 0.4490          | 0.8540   | 0.8514    | 0.8540 | 0.8521 |
| 0.5235        | 8.0   | 500  | 0.4651          | 0.8546   | 0.8578    | 0.8546 | 0.8536 |
| 0.5166        | 8.99  | 562  | 0.4501          | 0.8563   | 0.8551    | 0.8563 | 0.8523 |
| 0.486         | 10.0  | 625  | 0.4352          | 0.8647   | 0.8624    | 0.8647 | 0.8626 |
| 0.4882        | 10.99 | 687  | 0.4296          | 0.8613   | 0.8594    | 0.8613 | 0.8597 |
| 0.4426        | 12.0  | 750  | 0.4314          | 0.8579   | 0.8614    | 0.8579 | 0.8566 |
| 0.457         | 12.99 | 812  | 0.4226          | 0.8641   | 0.8642    | 0.8641 | 0.8624 |
| 0.4512        | 14.0  | 875  | 0.4319          | 0.8619   | 0.8653    | 0.8619 | 0.8591 |
| 0.4059        | 14.99 | 937  | 0.4124          | 0.8692   | 0.8675    | 0.8692 | 0.8681 |
| 0.4147        | 16.0  | 1000 | 0.3993          | 0.8732   | 0.8714    | 0.8732 | 0.8715 |
| 0.3721        | 16.99 | 1062 | 0.4116          | 0.8636   | 0.8609    | 0.8636 | 0.8604 |
| 0.3908        | 18.0  | 1125 | 0.4098          | 0.8675   | 0.8663    | 0.8675 | 0.8665 |
| 0.3836        | 18.99 | 1187 | 0.4188          | 0.8670   | 0.8651    | 0.8670 | 0.8651 |
| 0.3716        | 20.0  | 1250 | 0.4172          | 0.8681   | 0.8653    | 0.8681 | 0.8661 |
| 0.3484        | 20.99 | 1312 | 0.4404          | 0.8653   | 0.8649    | 0.8653 | 0.8628 |
| 0.3895        | 22.0  | 1375 | 0.4194          | 0.8698   | 0.8689    | 0.8698 | 0.8688 |
| 0.3452        | 22.99 | 1437 | 0.4447          | 0.8630   | 0.8634    | 0.8630 | 0.8621 |
| 0.341         | 24.0  | 1500 | 0.4253          | 0.8720   | 0.8722    | 0.8720 | 0.8712 |
| 0.3481        | 24.99 | 1562 | 0.4325          | 0.8681   | 0.8656    | 0.8681 | 0.8658 |
| 0.3115        | 26.0  | 1625 | 0.4340          | 0.8619   | 0.8609    | 0.8619 | 0.8603 |
| 0.313         | 26.99 | 1687 | 0.4329          | 0.8653   | 0.8644    | 0.8653 | 0.8644 |
| 0.3362        | 28.0  | 1750 | 0.4329          | 0.8653   | 0.8636    | 0.8653 | 0.8639 |
| 0.3056        | 28.99 | 1812 | 0.4342          | 0.8658   | 0.8645    | 0.8658 | 0.8644 |
| 0.3206        | 29.76 | 1860 | 0.4343          | 0.8664   | 0.8648    | 0.8664 | 0.8649 |


### Framework versions

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