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

This model is a fine-tuned version of [facebook/dinov2-base-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-base-imagenet1k-1-layer) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5267
- Accuracy: 0.8670
- Precision: 0.8645
- Recall: 0.8670
- F1: 0.8650

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8157        | 0.99  | 62   | 0.6740          | 0.7813   | 0.8046    | 0.7813 | 0.7853 |
| 0.8091        | 2.0   | 125  | 0.5948          | 0.8021   | 0.8016    | 0.8021 | 0.7950 |
| 0.6983        | 2.99  | 187  | 0.6016          | 0.7965   | 0.8077    | 0.7965 | 0.7909 |
| 0.6701        | 4.0   | 250  | 0.5676          | 0.7982   | 0.8016    | 0.7982 | 0.7954 |
| 0.5998        | 4.99  | 312  | 0.5116          | 0.8286   | 0.8401    | 0.8286 | 0.8302 |
| 0.5521        | 6.0   | 375  | 0.5155          | 0.8354   | 0.8375    | 0.8354 | 0.8325 |
| 0.5441        | 6.99  | 437  | 0.5574          | 0.8033   | 0.8104    | 0.8033 | 0.7980 |
| 0.5142        | 8.0   | 500  | 0.4818          | 0.8410   | 0.8418    | 0.8410 | 0.8376 |
| 0.5136        | 8.99  | 562  | 0.4914          | 0.8337   | 0.8353    | 0.8337 | 0.8317 |
| 0.4533        | 10.0  | 625  | 0.4740          | 0.8320   | 0.8335    | 0.8320 | 0.8295 |
| 0.4904        | 10.99 | 687  | 0.5075          | 0.8399   | 0.8409    | 0.8399 | 0.8375 |
| 0.4361        | 12.0  | 750  | 0.4552          | 0.8563   | 0.8554    | 0.8563 | 0.8540 |
| 0.414         | 12.99 | 812  | 0.5025          | 0.8365   | 0.8455    | 0.8365 | 0.8374 |
| 0.4114        | 14.0  | 875  | 0.4822          | 0.8467   | 0.8437    | 0.8467 | 0.8420 |
| 0.3878        | 14.99 | 937  | 0.4615          | 0.8574   | 0.8552    | 0.8574 | 0.8549 |
| 0.3756        | 16.0  | 1000 | 0.5017          | 0.8444   | 0.8523    | 0.8444 | 0.8449 |
| 0.3056        | 16.99 | 1062 | 0.4910          | 0.8517   | 0.8495    | 0.8517 | 0.8501 |
| 0.3255        | 18.0  | 1125 | 0.5206          | 0.8523   | 0.8505    | 0.8523 | 0.8491 |
| 0.3224        | 18.99 | 1187 | 0.5066          | 0.8450   | 0.8470    | 0.8450 | 0.8438 |
| 0.2763        | 20.0  | 1250 | 0.5043          | 0.8574   | 0.8519    | 0.8574 | 0.8534 |
| 0.2926        | 20.99 | 1312 | 0.5345          | 0.8546   | 0.8542    | 0.8546 | 0.8512 |
| 0.2824        | 22.0  | 1375 | 0.5320          | 0.8529   | 0.8523    | 0.8529 | 0.8517 |
| 0.2613        | 22.99 | 1437 | 0.5254          | 0.8563   | 0.8543    | 0.8563 | 0.8542 |
| 0.2292        | 24.0  | 1500 | 0.5553          | 0.8546   | 0.8529    | 0.8546 | 0.8528 |
| 0.2313        | 24.99 | 1562 | 0.5603          | 0.8602   | 0.8612    | 0.8602 | 0.8593 |
| 0.2143        | 26.0  | 1625 | 0.5267          | 0.8670   | 0.8645    | 0.8670 | 0.8650 |
| 0.2075        | 26.99 | 1687 | 0.5737          | 0.8574   | 0.8589    | 0.8574 | 0.8573 |
| 0.2121        | 28.0  | 1750 | 0.5748          | 0.8619   | 0.8601    | 0.8619 | 0.8604 |
| 0.1944        | 28.99 | 1812 | 0.5666          | 0.8647   | 0.8618    | 0.8647 | 0.8624 |
| 0.1866        | 29.76 | 1860 | 0.5676          | 0.8608   | 0.8583    | 0.8608 | 0.8589 |


### Framework versions

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