---
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-galaxy_mnist
  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-galaxy_mnist

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/galaxy_mnist dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2800
- Accuracy: 0.93
- Precision: 0.9301
- Recall: 0.93
- F1: 0.9300

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4569        | 0.99  | 31   | 0.4350          | 0.8145   | 0.8694    | 0.8145 | 0.8062 |
| 0.4173        | 1.98  | 62   | 0.3161          | 0.871    | 0.8848    | 0.871  | 0.8682 |
| 0.4318        | 2.98  | 93   | 0.3914          | 0.8285   | 0.8801    | 0.8285 | 0.8216 |
| 0.4238        | 4.0   | 125  | 0.3689          | 0.8485   | 0.8684    | 0.8485 | 0.8441 |
| 0.3735        | 4.99  | 156  | 0.2969          | 0.8735   | 0.8929    | 0.8735 | 0.8705 |
| 0.3371        | 5.98  | 187  | 0.2174          | 0.906    | 0.9136    | 0.906  | 0.9063 |
| 0.3069        | 6.98  | 218  | 0.2422          | 0.9055   | 0.9077    | 0.9055 | 0.9049 |
| 0.2526        | 8.0   | 250  | 0.2783          | 0.8905   | 0.9072    | 0.8905 | 0.8899 |
| 0.2753        | 8.99  | 281  | 0.2373          | 0.9155   | 0.9176    | 0.9155 | 0.9150 |
| 0.2704        | 9.98  | 312  | 0.2804          | 0.8865   | 0.9001    | 0.8865 | 0.8864 |
| 0.2417        | 10.98 | 343  | 0.2078          | 0.912    | 0.9126    | 0.912  | 0.9122 |
| 0.266         | 12.0  | 375  | 0.2004          | 0.918    | 0.9188    | 0.918  | 0.9183 |
| 0.2387        | 12.99 | 406  | 0.2255          | 0.9165   | 0.9196    | 0.9165 | 0.9160 |
| 0.2137        | 13.98 | 437  | 0.2208          | 0.9145   | 0.9169    | 0.9145 | 0.9147 |
| 0.2063        | 14.98 | 468  | 0.2078          | 0.9205   | 0.9210    | 0.9205 | 0.9204 |
| 0.2081        | 16.0  | 500  | 0.2658          | 0.9045   | 0.9115    | 0.9045 | 0.9037 |
| 0.1862        | 16.99 | 531  | 0.2425          | 0.914    | 0.9208    | 0.914  | 0.9143 |
| 0.1905        | 17.98 | 562  | 0.2398          | 0.912    | 0.9114    | 0.912  | 0.9116 |
| 0.1727        | 18.98 | 593  | 0.2999          | 0.9085   | 0.9100    | 0.9085 | 0.9084 |
| 0.1697        | 20.0  | 625  | 0.2520          | 0.9185   | 0.9197    | 0.9185 | 0.9183 |
| 0.161         | 20.99 | 656  | 0.2471          | 0.9205   | 0.9216    | 0.9205 | 0.9205 |
| 0.1363        | 21.98 | 687  | 0.2449          | 0.922    | 0.9224    | 0.922  | 0.9222 |
| 0.1533        | 22.98 | 718  | 0.2780          | 0.917    | 0.9179    | 0.917  | 0.9173 |
| 0.1324        | 24.0  | 750  | 0.2683          | 0.917    | 0.9184    | 0.917  | 0.9170 |
| 0.1291        | 24.99 | 781  | 0.2651          | 0.924    | 0.9243    | 0.924  | 0.9240 |
| 0.1112        | 25.98 | 812  | 0.3036          | 0.924    | 0.9245    | 0.924  | 0.9240 |
| 0.1175        | 26.98 | 843  | 0.2818          | 0.927    | 0.9270    | 0.927  | 0.9269 |
| 0.1214        | 28.0  | 875  | 0.2800          | 0.93     | 0.9301    | 0.93   | 0.9300 |
| 0.0953        | 28.99 | 906  | 0.3168          | 0.9245   | 0.9244    | 0.9245 | 0.9244 |
| 0.0955        | 29.76 | 930  | 0.3216          | 0.925    | 0.9249    | 0.925  | 0.9249 |


### Framework versions

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