---
license: apache-2.0
base_model: facebook/dinov2-small
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: dinov2-small-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. -->

# dinov2-small-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4852
- Accuracy: 0.8613
- Precision: 0.8626
- Recall: 0.8613
- F1: 0.8615

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.279         | 0.99  | 31   | 0.9926          | 0.6454   | 0.6589    | 0.6454 | 0.6242 |
| 0.8187        | 1.98  | 62   | 0.6014          | 0.7948   | 0.8151    | 0.7948 | 0.7948 |
| 0.77          | 2.98  | 93   | 0.6323          | 0.7818   | 0.7928    | 0.7818 | 0.7777 |
| 0.6743        | 4.0   | 125  | 0.5555          | 0.8140   | 0.8149    | 0.8140 | 0.8083 |
| 0.6407        | 4.99  | 156  | 0.5732          | 0.8078   | 0.8174    | 0.8078 | 0.8096 |
| 0.64          | 5.98  | 187  | 0.4912          | 0.8360   | 0.8344    | 0.8360 | 0.8321 |
| 0.5685        | 6.98  | 218  | 0.5089          | 0.8185   | 0.8195    | 0.8185 | 0.8163 |
| 0.5438        | 8.0   | 250  | 0.4806          | 0.8320   | 0.8325    | 0.8320 | 0.8293 |
| 0.5455        | 8.99  | 281  | 0.4781          | 0.8410   | 0.8442    | 0.8410 | 0.8406 |
| 0.5002        | 9.98  | 312  | 0.4403          | 0.8478   | 0.8457    | 0.8478 | 0.8452 |
| 0.5003        | 10.98 | 343  | 0.5079          | 0.8151   | 0.8355    | 0.8151 | 0.8156 |
| 0.4828        | 12.0  | 375  | 0.5307          | 0.8191   | 0.8197    | 0.8191 | 0.8147 |
| 0.4674        | 12.99 | 406  | 0.4732          | 0.8444   | 0.8450    | 0.8444 | 0.8431 |
| 0.4646        | 13.98 | 437  | 0.4952          | 0.8281   | 0.8342    | 0.8281 | 0.8251 |
| 0.4477        | 14.98 | 468  | 0.4607          | 0.8523   | 0.8516    | 0.8523 | 0.8514 |
| 0.4224        | 16.0  | 500  | 0.4514          | 0.8506   | 0.8516    | 0.8506 | 0.8495 |
| 0.3751        | 16.99 | 531  | 0.4665          | 0.8484   | 0.8480    | 0.8484 | 0.8472 |
| 0.3874        | 17.98 | 562  | 0.4462          | 0.8489   | 0.8489    | 0.8489 | 0.8477 |
| 0.3675        | 18.98 | 593  | 0.4674          | 0.8484   | 0.8508    | 0.8484 | 0.8471 |
| 0.3434        | 20.0  | 625  | 0.4644          | 0.8512   | 0.8486    | 0.8512 | 0.8462 |
| 0.3332        | 20.99 | 656  | 0.4711          | 0.8557   | 0.8548    | 0.8557 | 0.8525 |
| 0.3187        | 21.98 | 687  | 0.4665          | 0.8534   | 0.8539    | 0.8534 | 0.8524 |
| 0.3039        | 22.98 | 718  | 0.5015          | 0.8439   | 0.8427    | 0.8439 | 0.8423 |
| 0.282         | 24.0  | 750  | 0.4783          | 0.8563   | 0.8563    | 0.8563 | 0.8559 |
| 0.2843        | 24.99 | 781  | 0.5064          | 0.8534   | 0.8519    | 0.8534 | 0.8514 |
| 0.2661        | 25.98 | 812  | 0.5021          | 0.8484   | 0.8476    | 0.8484 | 0.8460 |
| 0.2595        | 26.98 | 843  | 0.4852          | 0.8613   | 0.8626    | 0.8613 | 0.8615 |
| 0.2442        | 28.0  | 875  | 0.4903          | 0.8568   | 0.8546    | 0.8568 | 0.8543 |
| 0.2477        | 28.99 | 906  | 0.4781          | 0.8585   | 0.8569    | 0.8585 | 0.8570 |
| 0.2437        | 29.76 | 930  | 0.4772          | 0.8585   | 0.8580    | 0.8585 | 0.8577 |


### Framework versions

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