---
license: apache-2.0
base_model: facebook/convnextv2-nano-22k-224
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: convnextv2-nano-22k-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-nano-22k-224-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/convnextv2-nano-22k-224](https://huggingface.co/facebook/convnextv2-nano-22k-224) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4386
- Accuracy: 0.8687
- Precision: 0.8680
- Recall: 0.8687
- F1: 0.8662

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.7173        | 0.99  | 62   | 1.5497          | 0.4617   | 0.4305    | 0.4617 | 0.4119 |
| 0.9692        | 2.0   | 125  | 0.8180          | 0.7306   | 0.7295    | 0.7306 | 0.7246 |
| 0.7643        | 2.99  | 187  | 0.6075          | 0.7931   | 0.7921    | 0.7931 | 0.7880 |
| 0.6282        | 4.0   | 250  | 0.5506          | 0.8151   | 0.8112    | 0.8151 | 0.8068 |
| 0.5712        | 4.99  | 312  | 0.5769          | 0.7982   | 0.8129    | 0.7982 | 0.8002 |
| 0.5702        | 6.0   | 375  | 0.5195          | 0.8315   | 0.8351    | 0.8315 | 0.8225 |
| 0.5423        | 6.99  | 437  | 0.4890          | 0.8331   | 0.8296    | 0.8331 | 0.8303 |
| 0.4989        | 8.0   | 500  | 0.4764          | 0.8371   | 0.8361    | 0.8371 | 0.8342 |
| 0.4997        | 8.99  | 562  | 0.4725          | 0.8405   | 0.8393    | 0.8405 | 0.8365 |
| 0.476         | 10.0  | 625  | 0.4582          | 0.8467   | 0.8465    | 0.8467 | 0.8435 |
| 0.4603        | 10.99 | 687  | 0.4460          | 0.8489   | 0.8464    | 0.8489 | 0.8472 |
| 0.4318        | 12.0  | 750  | 0.4398          | 0.8534   | 0.8519    | 0.8534 | 0.8515 |
| 0.4387        | 12.99 | 812  | 0.4575          | 0.8613   | 0.8598    | 0.8613 | 0.8577 |
| 0.4357        | 14.0  | 875  | 0.4398          | 0.8568   | 0.8541    | 0.8568 | 0.8532 |
| 0.3944        | 14.99 | 937  | 0.4425          | 0.8540   | 0.8533    | 0.8540 | 0.8524 |
| 0.3961        | 16.0  | 1000 | 0.4394          | 0.8574   | 0.8555    | 0.8574 | 0.8542 |
| 0.3557        | 16.99 | 1062 | 0.4510          | 0.8523   | 0.8497    | 0.8523 | 0.8481 |
| 0.3881        | 18.0  | 1125 | 0.4399          | 0.8591   | 0.8590    | 0.8591 | 0.8577 |
| 0.3663        | 18.99 | 1187 | 0.4631          | 0.8546   | 0.8545    | 0.8546 | 0.8524 |
| 0.3691        | 20.0  | 1250 | 0.4439          | 0.8608   | 0.8585    | 0.8608 | 0.8577 |
| 0.3443        | 20.99 | 1312 | 0.4524          | 0.8568   | 0.8555    | 0.8568 | 0.8545 |
| 0.3728        | 22.0  | 1375 | 0.4386          | 0.8687   | 0.8680    | 0.8687 | 0.8662 |
| 0.3309        | 22.99 | 1437 | 0.4506          | 0.8585   | 0.8578    | 0.8585 | 0.8573 |
| 0.33          | 24.0  | 1500 | 0.4426          | 0.8630   | 0.8613    | 0.8630 | 0.8618 |
| 0.3541        | 24.99 | 1562 | 0.4625          | 0.8585   | 0.8561    | 0.8585 | 0.8560 |
| 0.2968        | 26.0  | 1625 | 0.4460          | 0.8613   | 0.8593    | 0.8613 | 0.8590 |
| 0.3031        | 26.99 | 1687 | 0.4492          | 0.8641   | 0.8630    | 0.8641 | 0.8628 |
| 0.3207        | 28.0  | 1750 | 0.4480          | 0.8664   | 0.8640    | 0.8664 | 0.8637 |
| 0.2949        | 28.99 | 1812 | 0.4478          | 0.8636   | 0.8614    | 0.8636 | 0.8615 |
| 0.2985        | 29.76 | 1860 | 0.4477          | 0.8636   | 0.8612    | 0.8636 | 0.8614 |


### Framework versions

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