---
license: apache-2.0
base_model: facebook/dinov2-small-imagenet1k-1-layer
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: dinov2-small-imagenet1k-1-layer-finetuned-galaxy10-decals
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# dinov2-small-imagenet1k-1-layer-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/dinov2-small-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-small-imagenet1k-1-layer) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5373
- Accuracy: 0.8563
- Precision: 0.8536
- Recall: 0.8563
- F1: 0.8543

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0027        | 0.99  | 62   | 0.8262          | 0.7080   | 0.7231    | 0.7080 | 0.7017 |
| 0.8374        | 2.0   | 125  | 0.6129          | 0.7948   | 0.7960    | 0.7948 | 0.7899 |
| 0.7753        | 2.99  | 187  | 0.6555          | 0.7892   | 0.7921    | 0.7892 | 0.7787 |
| 0.7165        | 4.0   | 250  | 0.5862          | 0.8005   | 0.8053    | 0.8005 | 0.7970 |
| 0.6477        | 4.99  | 312  | 0.6183          | 0.7965   | 0.8119    | 0.7965 | 0.7985 |
| 0.6892        | 6.0   | 375  | 0.5310          | 0.8247   | 0.8275    | 0.8247 | 0.8195 |
| 0.6171        | 6.99  | 437  | 0.5678          | 0.8083   | 0.8157    | 0.8083 | 0.8022 |
| 0.55          | 8.0   | 500  | 0.4961          | 0.8326   | 0.8353    | 0.8326 | 0.8316 |
| 0.5615        | 8.99  | 562  | 0.5033          | 0.8309   | 0.8312    | 0.8309 | 0.8274 |
| 0.5107        | 10.0  | 625  | 0.5162          | 0.8191   | 0.8164    | 0.8191 | 0.8152 |
| 0.5237        | 10.99 | 687  | 0.4790          | 0.8422   | 0.8452    | 0.8422 | 0.8381 |
| 0.4954        | 12.0  | 750  | 0.4782          | 0.8422   | 0.8430    | 0.8422 | 0.8373 |
| 0.4887        | 12.99 | 812  | 0.4689          | 0.8371   | 0.8395    | 0.8371 | 0.8358 |
| 0.4629        | 14.0  | 875  | 0.4541          | 0.8523   | 0.8500    | 0.8523 | 0.8502 |
| 0.4486        | 14.99 | 937  | 0.4755          | 0.8405   | 0.8400    | 0.8405 | 0.8394 |
| 0.4361        | 16.0  | 1000 | 0.4763          | 0.8371   | 0.8392    | 0.8371 | 0.8370 |
| 0.3833        | 16.99 | 1062 | 0.4982          | 0.8416   | 0.8429    | 0.8416 | 0.8396 |
| 0.3788        | 18.0  | 1125 | 0.5632          | 0.8292   | 0.8365    | 0.8292 | 0.8267 |
| 0.3722        | 18.99 | 1187 | 0.5162          | 0.8388   | 0.8364    | 0.8388 | 0.8357 |
| 0.3467        | 20.0  | 1250 | 0.5125          | 0.8399   | 0.8357    | 0.8399 | 0.8342 |
| 0.3518        | 20.99 | 1312 | 0.5569          | 0.8309   | 0.8327    | 0.8309 | 0.8276 |
| 0.3432        | 22.0  | 1375 | 0.5032          | 0.8484   | 0.8451    | 0.8484 | 0.8454 |
| 0.3067        | 22.99 | 1437 | 0.5246          | 0.8433   | 0.8462    | 0.8433 | 0.8433 |
| 0.2923        | 24.0  | 1500 | 0.5363          | 0.8467   | 0.8482    | 0.8467 | 0.8464 |
| 0.303         | 24.99 | 1562 | 0.5435          | 0.8484   | 0.8453    | 0.8484 | 0.8457 |
| 0.2523        | 26.0  | 1625 | 0.5500          | 0.8444   | 0.8422    | 0.8444 | 0.8419 |
| 0.2523        | 26.99 | 1687 | 0.5369          | 0.8529   | 0.8533    | 0.8529 | 0.8529 |
| 0.262         | 28.0  | 1750 | 0.5373          | 0.8563   | 0.8536    | 0.8563 | 0.8543 |
| 0.232         | 28.99 | 1812 | 0.5384          | 0.8529   | 0.8509    | 0.8529 | 0.8516 |
| 0.2278        | 29.76 | 1860 | 0.5429          | 0.8512   | 0.8489    | 0.8512 | 0.8495 |


### Framework versions

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