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

This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-224](https://huggingface.co/facebook/convnextv2-tiny-22k-224) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4373
- Accuracy: 0.8636
- Precision: 0.8625
- Recall: 0.8636
- F1: 0.8603

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.5665        | 0.99  | 62   | 1.3996          | 0.5287   | 0.5180    | 0.5287 | 0.4897 |
| 0.8598        | 2.0   | 125  | 0.7433          | 0.7463   | 0.7490    | 0.7463 | 0.7396 |
| 0.7163        | 2.99  | 187  | 0.5703          | 0.7948   | 0.7919    | 0.7948 | 0.7863 |
| 0.5858        | 4.0   | 250  | 0.5194          | 0.8269   | 0.8292    | 0.8269 | 0.8190 |
| 0.5382        | 4.99  | 312  | 0.4936          | 0.8309   | 0.8314    | 0.8309 | 0.8302 |
| 0.5546        | 6.0   | 375  | 0.5054          | 0.8292   | 0.8366    | 0.8292 | 0.8234 |
| 0.5067        | 6.99  | 437  | 0.4817          | 0.8281   | 0.8324    | 0.8281 | 0.8278 |
| 0.4617        | 8.0   | 500  | 0.4565          | 0.8501   | 0.8545    | 0.8501 | 0.8497 |
| 0.4619        | 8.99  | 562  | 0.4382          | 0.8534   | 0.8520    | 0.8534 | 0.8498 |
| 0.4416        | 10.0  | 625  | 0.4330          | 0.8529   | 0.8505    | 0.8529 | 0.8504 |
| 0.4267        | 10.99 | 687  | 0.4274          | 0.8574   | 0.8575    | 0.8574 | 0.8566 |
| 0.3919        | 12.0  | 750  | 0.4407          | 0.8585   | 0.8604    | 0.8585 | 0.8563 |
| 0.3929        | 12.99 | 812  | 0.4373          | 0.8636   | 0.8625    | 0.8636 | 0.8603 |
| 0.3989        | 14.0  | 875  | 0.4351          | 0.8585   | 0.8602    | 0.8585 | 0.8577 |
| 0.3426        | 14.99 | 937  | 0.4476          | 0.8495   | 0.8500    | 0.8495 | 0.8484 |
| 0.361         | 16.0  | 1000 | 0.4463          | 0.8517   | 0.8505    | 0.8517 | 0.8501 |
| 0.2996        | 16.99 | 1062 | 0.4694          | 0.8596   | 0.8604    | 0.8596 | 0.8579 |
| 0.3394        | 18.0  | 1125 | 0.4494          | 0.8523   | 0.8526    | 0.8523 | 0.8517 |
| 0.3207        | 18.99 | 1187 | 0.4863          | 0.8506   | 0.8502    | 0.8506 | 0.8496 |
| 0.2993        | 20.0  | 1250 | 0.4748          | 0.8551   | 0.8516    | 0.8551 | 0.8521 |
| 0.287         | 20.99 | 1312 | 0.4980          | 0.8467   | 0.8436    | 0.8467 | 0.8434 |
| 0.3331        | 22.0  | 1375 | 0.4829          | 0.8546   | 0.8530    | 0.8546 | 0.8519 |
| 0.2852        | 22.99 | 1437 | 0.4943          | 0.8512   | 0.8520    | 0.8512 | 0.8508 |
| 0.2813        | 24.0  | 1500 | 0.4796          | 0.8574   | 0.8574    | 0.8574 | 0.8568 |
| 0.2807        | 24.99 | 1562 | 0.4811          | 0.8596   | 0.8576    | 0.8596 | 0.8576 |
| 0.2609        | 26.0  | 1625 | 0.4786          | 0.8608   | 0.8589    | 0.8608 | 0.8592 |
| 0.2571        | 26.99 | 1687 | 0.4777          | 0.8608   | 0.8605    | 0.8608 | 0.8602 |
| 0.2807        | 28.0  | 1750 | 0.4879          | 0.8596   | 0.8580    | 0.8596 | 0.8582 |
| 0.2578        | 28.99 | 1812 | 0.4829          | 0.8557   | 0.8550    | 0.8557 | 0.8549 |
| 0.2543        | 29.76 | 1860 | 0.4833          | 0.8563   | 0.8555    | 0.8563 | 0.8554 |


### Framework versions

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