---
license: apache-2.0
base_model: facebook/convnextv2-atto-1k-224
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: convnextv2-atto-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-atto-1k-224-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/convnextv2-atto-1k-224](https://huggingface.co/facebook/convnextv2-atto-1k-224) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4668
- Accuracy: 0.8461
- Precision: 0.8444
- Recall: 0.8461
- F1: 0.8442

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.0062        | 0.99  | 62   | 1.8928          | 0.3450   | 0.3432    | 0.3450 | 0.2956 |
| 1.1323        | 2.0   | 125  | 1.0026          | 0.6590   | 0.6634    | 0.6590 | 0.6399 |
| 0.8977        | 2.99  | 187  | 0.7348          | 0.7486   | 0.7415    | 0.7486 | 0.7399 |
| 0.7119        | 4.0   | 250  | 0.6395          | 0.7892   | 0.7878    | 0.7892 | 0.7770 |
| 0.6393        | 4.99  | 312  | 0.5801          | 0.7971   | 0.7916    | 0.7971 | 0.7915 |
| 0.6463        | 6.0   | 375  | 0.5958          | 0.7976   | 0.8147    | 0.7976 | 0.7909 |
| 0.6197        | 6.99  | 437  | 0.5363          | 0.8151   | 0.8119    | 0.8151 | 0.8112 |
| 0.5779        | 8.0   | 500  | 0.5276          | 0.8207   | 0.8205    | 0.8207 | 0.8185 |
| 0.5841        | 8.99  | 562  | 0.5197          | 0.8185   | 0.8203    | 0.8185 | 0.8157 |
| 0.5597        | 10.0  | 625  | 0.5025          | 0.8253   | 0.8192    | 0.8253 | 0.8193 |
| 0.5437        | 10.99 | 687  | 0.4912          | 0.8309   | 0.8295    | 0.8309 | 0.8296 |
| 0.5242        | 12.0  | 750  | 0.5001          | 0.8275   | 0.8303    | 0.8275 | 0.8245 |
| 0.5029        | 12.99 | 812  | 0.5075          | 0.8241   | 0.8228    | 0.8241 | 0.8208 |
| 0.5396        | 14.0  | 875  | 0.4784          | 0.8393   | 0.8395    | 0.8393 | 0.8371 |
| 0.4746        | 14.99 | 937  | 0.4727          | 0.8331   | 0.8318    | 0.8331 | 0.8317 |
| 0.4786        | 16.0  | 1000 | 0.4856          | 0.8331   | 0.8308    | 0.8331 | 0.8300 |
| 0.4338        | 16.99 | 1062 | 0.4884          | 0.8337   | 0.8333    | 0.8337 | 0.8309 |
| 0.4772        | 18.0  | 1125 | 0.4618          | 0.8405   | 0.8370    | 0.8405 | 0.8377 |
| 0.4733        | 18.99 | 1187 | 0.4740          | 0.8393   | 0.8394    | 0.8393 | 0.8381 |
| 0.4475        | 20.0  | 1250 | 0.4678          | 0.8388   | 0.8349    | 0.8388 | 0.8345 |
| 0.4229        | 20.99 | 1312 | 0.4881          | 0.8331   | 0.8317    | 0.8331 | 0.8303 |
| 0.46          | 22.0  | 1375 | 0.4728          | 0.8410   | 0.8382    | 0.8410 | 0.8371 |
| 0.4298        | 22.99 | 1437 | 0.4642          | 0.8360   | 0.8348    | 0.8360 | 0.8345 |
| 0.4225        | 24.0  | 1500 | 0.4706          | 0.8371   | 0.8368    | 0.8371 | 0.8359 |
| 0.426         | 24.99 | 1562 | 0.4733          | 0.8399   | 0.8367    | 0.8399 | 0.8371 |
| 0.3839        | 26.0  | 1625 | 0.4682          | 0.8444   | 0.8423    | 0.8444 | 0.8422 |
| 0.4007        | 26.99 | 1687 | 0.4665          | 0.8382   | 0.8371    | 0.8382 | 0.8367 |
| 0.4245        | 28.0  | 1750 | 0.4695          | 0.8388   | 0.8357    | 0.8388 | 0.8358 |
| 0.3868        | 28.99 | 1812 | 0.4668          | 0.8461   | 0.8444    | 0.8461 | 0.8442 |
| 0.3933        | 29.76 | 1860 | 0.4657          | 0.8461   | 0.8442    | 0.8461 | 0.8440 |


### Framework versions

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