---
license: apache-2.0
base_model: facebook/dinov2-large
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: dinov2-large-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-large-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5869
- Accuracy: 0.8737
- Precision: 0.8722
- Recall: 0.8737
- F1: 0.8722

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.7564        | 0.99  | 62   | 0.6187          | 0.7976   | 0.8171    | 0.7976 | 0.7990 |
| 0.7766        | 2.0   | 125  | 0.6102          | 0.7852   | 0.8052    | 0.7852 | 0.7782 |
| 0.7103        | 2.99  | 187  | 0.5744          | 0.8089   | 0.8140    | 0.8089 | 0.8032 |
| 0.6704        | 4.0   | 250  | 0.6859          | 0.7745   | 0.7899    | 0.7745 | 0.7663 |
| 0.599         | 4.99  | 312  | 0.4729          | 0.8377   | 0.8412    | 0.8377 | 0.8359 |
| 0.565         | 6.0   | 375  | 0.4465          | 0.8517   | 0.8542    | 0.8517 | 0.8507 |
| 0.5576        | 6.99  | 437  | 0.4479          | 0.8484   | 0.8565    | 0.8484 | 0.8452 |
| 0.4966        | 8.0   | 500  | 0.4870          | 0.8388   | 0.8399    | 0.8388 | 0.8363 |
| 0.4667        | 8.99  | 562  | 0.4763          | 0.8444   | 0.8496    | 0.8444 | 0.8443 |
| 0.4264        | 10.0  | 625  | 0.4802          | 0.8377   | 0.8378    | 0.8377 | 0.8324 |
| 0.445         | 10.99 | 687  | 0.5246          | 0.8377   | 0.8383    | 0.8377 | 0.8343 |
| 0.3935        | 12.0  | 750  | 0.4883          | 0.8439   | 0.8519    | 0.8439 | 0.8434 |
| 0.374         | 12.99 | 812  | 0.4511          | 0.8568   | 0.8603    | 0.8568 | 0.8569 |
| 0.3551        | 14.0  | 875  | 0.5153          | 0.8546   | 0.8517    | 0.8546 | 0.8496 |
| 0.3573        | 14.99 | 937  | 0.4705          | 0.8579   | 0.8554    | 0.8579 | 0.8559 |
| 0.3385        | 16.0  | 1000 | 0.4547          | 0.8517   | 0.8535    | 0.8517 | 0.8517 |
| 0.2764        | 16.99 | 1062 | 0.5189          | 0.8529   | 0.8544    | 0.8529 | 0.8513 |
| 0.2895        | 18.0  | 1125 | 0.5393          | 0.8602   | 0.8587    | 0.8602 | 0.8586 |
| 0.2738        | 18.99 | 1187 | 0.5554          | 0.8405   | 0.8436    | 0.8405 | 0.8381 |
| 0.2563        | 20.0  | 1250 | 0.5478          | 0.8608   | 0.8573    | 0.8608 | 0.8574 |
| 0.2375        | 20.99 | 1312 | 0.5512          | 0.8664   | 0.8651    | 0.8664 | 0.8622 |
| 0.2599        | 22.0  | 1375 | 0.5317          | 0.8625   | 0.8607    | 0.8625 | 0.8599 |
| 0.2146        | 22.99 | 1437 | 0.5972          | 0.8568   | 0.8567    | 0.8568 | 0.8559 |
| 0.2132        | 24.0  | 1500 | 0.5934          | 0.8636   | 0.8617    | 0.8636 | 0.8606 |
| 0.2036        | 24.99 | 1562 | 0.5923          | 0.8664   | 0.8662    | 0.8664 | 0.8658 |
| 0.1971        | 26.0  | 1625 | 0.5839          | 0.8630   | 0.8621    | 0.8630 | 0.8621 |
| 0.1878        | 26.99 | 1687 | 0.5907          | 0.8625   | 0.8669    | 0.8625 | 0.8640 |
| 0.1922        | 28.0  | 1750 | 0.6058          | 0.8692   | 0.8684    | 0.8692 | 0.8680 |
| 0.1854        | 28.99 | 1812 | 0.6014          | 0.8670   | 0.8653    | 0.8670 | 0.8655 |
| 0.1688        | 29.76 | 1860 | 0.5869          | 0.8737   | 0.8722    | 0.8737 | 0.8722 |


### Framework versions

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