---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: dinov2-Base-finetuned-food101
  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-Base-finetuned-food101

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0924
- Accuracy: 0.98
- F1: 0.9809

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.675         | 1.0   | 625  | 0.1778          | 0.938    | 0.9399 |
| 0.5284        | 2.0   | 1250 | 0.1248          | 0.9613   | 0.9615 |
| 0.3455        | 3.0   | 1875 | 0.1548          | 0.9513   | 0.9523 |
| 0.1915        | 4.0   | 2500 | 0.1321          | 0.9567   | 0.9586 |
| 0.1953        | 5.0   | 3125 | 0.0772          | 0.978    | 0.9784 |
| 0.183         | 6.0   | 3750 | 0.0829          | 0.9773   | 0.9781 |
| 0.1513        | 7.0   | 4375 | 0.1134          | 0.972    | 0.9735 |
| 0.1222        | 8.0   | 5000 | 0.1164          | 0.972    | 0.9729 |
| 0.2001        | 9.0   | 5625 | 0.0865          | 0.9773   | 0.9783 |
| 0.0618        | 10.0  | 6250 | 0.0924          | 0.98     | 0.9809 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1