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

This model is a fine-tuned version of [facebook/convnextv2-pico-1k-224](https://huggingface.co/facebook/convnextv2-pico-1k-224) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5795
- Accuracy: 0.8546
- Precision: 0.8565
- Recall: 0.8546
- F1: 0.8545

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0752        | 0.99  | 62   | 0.9584          | 0.6697   | 0.6820    | 0.6697 | 0.6581 |
| 0.814         | 2.0   | 125  | 0.6716          | 0.7728   | 0.7780    | 0.7728 | 0.7695 |
| 0.7289        | 2.99  | 187  | 0.6071          | 0.7959   | 0.8093    | 0.7959 | 0.7943 |
| 0.6444        | 4.0   | 250  | 0.5873          | 0.8055   | 0.8103    | 0.8055 | 0.8019 |
| 0.5855        | 4.99  | 312  | 0.5889          | 0.8106   | 0.8226    | 0.8106 | 0.8106 |
| 0.5778        | 6.0   | 375  | 0.5039          | 0.8281   | 0.8321    | 0.8281 | 0.8274 |
| 0.5575        | 6.99  | 437  | 0.5162          | 0.8140   | 0.8235    | 0.8140 | 0.8148 |
| 0.5011        | 8.0   | 500  | 0.5369          | 0.8207   | 0.8234    | 0.8207 | 0.8205 |
| 0.4968        | 8.99  | 562  | 0.5152          | 0.8292   | 0.8282    | 0.8292 | 0.8270 |
| 0.4593        | 10.0  | 625  | 0.4854          | 0.8382   | 0.8408    | 0.8382 | 0.8367 |
| 0.4442        | 10.99 | 687  | 0.4923          | 0.8416   | 0.8423    | 0.8416 | 0.8411 |
| 0.4071        | 12.0  | 750  | 0.5312          | 0.8377   | 0.8356    | 0.8377 | 0.8331 |
| 0.4057        | 12.99 | 812  | 0.4954          | 0.8433   | 0.8449    | 0.8433 | 0.8416 |
| 0.4074        | 14.0  | 875  | 0.4735          | 0.8534   | 0.8509    | 0.8534 | 0.8493 |
| 0.3709        | 14.99 | 937  | 0.4977          | 0.8461   | 0.8450    | 0.8461 | 0.8442 |
| 0.3467        | 16.0  | 1000 | 0.5364          | 0.8286   | 0.8278    | 0.8286 | 0.8274 |
| 0.3129        | 16.99 | 1062 | 0.5695          | 0.8422   | 0.8413    | 0.8422 | 0.8376 |
| 0.3242        | 18.0  | 1125 | 0.5131          | 0.8455   | 0.8469    | 0.8455 | 0.8450 |
| 0.3046        | 18.99 | 1187 | 0.5553          | 0.8399   | 0.8382    | 0.8399 | 0.8371 |
| 0.2805        | 20.0  | 1250 | 0.5871          | 0.8523   | 0.8532    | 0.8523 | 0.8456 |
| 0.2776        | 20.99 | 1312 | 0.5428          | 0.8433   | 0.8404    | 0.8433 | 0.8404 |
| 0.2975        | 22.0  | 1375 | 0.5624          | 0.8393   | 0.8344    | 0.8393 | 0.8359 |
| 0.268         | 22.99 | 1437 | 0.5485          | 0.8495   | 0.8518    | 0.8495 | 0.8498 |
| 0.2535        | 24.0  | 1500 | 0.6135          | 0.8382   | 0.8367    | 0.8382 | 0.8358 |
| 0.2543        | 24.99 | 1562 | 0.6103          | 0.8393   | 0.8389    | 0.8393 | 0.8375 |
| 0.2283        | 26.0  | 1625 | 0.5639          | 0.8484   | 0.8499    | 0.8484 | 0.8480 |
| 0.2341        | 26.99 | 1687 | 0.5795          | 0.8546   | 0.8565    | 0.8546 | 0.8545 |
| 0.2404        | 28.0  | 1750 | 0.5794          | 0.8534   | 0.8515    | 0.8534 | 0.8511 |
| 0.2168        | 28.99 | 1812 | 0.5652          | 0.8546   | 0.8525    | 0.8546 | 0.8524 |
| 0.2057        | 29.76 | 1860 | 0.5650          | 0.8546   | 0.8519    | 0.8546 | 0.8518 |


### Framework versions

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