---
license: apache-2.0
base_model: facebook/convnextv2-nano-22k-384
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: convnextv2-nano-22k-384-finetuned-galaxy10-decals
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# convnextv2-nano-22k-384-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/convnextv2-nano-22k-384](https://huggingface.co/facebook/convnextv2-nano-22k-384) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4057
- Accuracy: 0.8681
- Precision: 0.8662
- Recall: 0.8681
- F1: 0.8650

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6939        | 0.99  | 62   | 1.5326          | 0.4656   | 0.4580    | 0.4656 | 0.4176 |
| 0.9882        | 2.0   | 125  | 0.8491          | 0.7142   | 0.7196    | 0.7142 | 0.7066 |
| 0.7595        | 2.99  | 187  | 0.6041          | 0.7993   | 0.7990    | 0.7993 | 0.7947 |
| 0.6097        | 4.0   | 250  | 0.5397          | 0.8134   | 0.8078    | 0.8134 | 0.8069 |
| 0.5565        | 4.99  | 312  | 0.4990          | 0.8286   | 0.8269    | 0.8286 | 0.8268 |
| 0.5822        | 6.0   | 375  | 0.4684          | 0.8427   | 0.8425    | 0.8427 | 0.8374 |
| 0.5244        | 6.99  | 437  | 0.4484          | 0.8512   | 0.8476    | 0.8512 | 0.8483 |
| 0.4957        | 8.0   | 500  | 0.4487          | 0.8506   | 0.8543    | 0.8506 | 0.8514 |
| 0.4857        | 8.99  | 562  | 0.4369          | 0.8579   | 0.8572    | 0.8579 | 0.8545 |
| 0.4634        | 10.0  | 625  | 0.4104          | 0.8658   | 0.8630    | 0.8658 | 0.8639 |
| 0.4433        | 10.99 | 687  | 0.4117          | 0.8664   | 0.8649    | 0.8664 | 0.8651 |
| 0.4267        | 12.0  | 750  | 0.4096          | 0.8664   | 0.8632    | 0.8664 | 0.8634 |
| 0.4201        | 12.99 | 812  | 0.4212          | 0.8658   | 0.8645    | 0.8658 | 0.8631 |
| 0.4176        | 14.0  | 875  | 0.4057          | 0.8681   | 0.8662    | 0.8681 | 0.8650 |
| 0.3717        | 14.99 | 937  | 0.4299          | 0.8568   | 0.8547    | 0.8568 | 0.8551 |
| 0.3759        | 16.0  | 1000 | 0.4446          | 0.8585   | 0.8563    | 0.8585 | 0.8555 |
| 0.3264        | 16.99 | 1062 | 0.4276          | 0.8647   | 0.8630    | 0.8647 | 0.8623 |
| 0.3573        | 18.0  | 1125 | 0.4199          | 0.8641   | 0.8621    | 0.8641 | 0.8610 |
| 0.3356        | 18.99 | 1187 | 0.4388          | 0.8585   | 0.8597    | 0.8585 | 0.8579 |
| 0.3313        | 20.0  | 1250 | 0.4385          | 0.8602   | 0.8585    | 0.8602 | 0.8571 |
| 0.3044        | 20.99 | 1312 | 0.4485          | 0.8585   | 0.8578    | 0.8585 | 0.8560 |
| 0.3525        | 22.0  | 1375 | 0.4303          | 0.8647   | 0.8641    | 0.8647 | 0.8634 |
| 0.3207        | 22.99 | 1437 | 0.4525          | 0.8608   | 0.8597    | 0.8608 | 0.8591 |
| 0.3044        | 24.0  | 1500 | 0.4417          | 0.8591   | 0.8578    | 0.8591 | 0.8579 |
| 0.3088        | 24.99 | 1562 | 0.4626          | 0.8608   | 0.8586    | 0.8608 | 0.8582 |
| 0.2897        | 26.0  | 1625 | 0.4524          | 0.8630   | 0.8606    | 0.8630 | 0.8606 |
| 0.2823        | 26.99 | 1687 | 0.4433          | 0.8670   | 0.8657    | 0.8670 | 0.8657 |
| 0.2928        | 28.0  | 1750 | 0.4479          | 0.8658   | 0.8629    | 0.8658 | 0.8631 |
| 0.2695        | 28.99 | 1812 | 0.4455          | 0.8658   | 0.8637    | 0.8658 | 0.8639 |
| 0.274         | 29.76 | 1860 | 0.4449          | 0.8630   | 0.8607    | 0.8630 | 0.8610 |


### Framework versions

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