---
license: apache-2.0
base_model: facebook/dinov2-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: DinoVdeau-large-2024_10_25-prova_batch-size8_freeze_monolabel
  results: []
---

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# DinoVdeau-large-2024_10_25-prova_batch-size8_freeze_monolabel

This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8116
- F1 Micro: 0.5
- F1 Macro: 0.2126
- Accuracy: 0.5
- Learning Rate: 0.001

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy | Rate  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:-----:|
| No log        | 1.0   | 7    | 2.7061          | 0.5      | 0.2790   | 0.5      | 0.001 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.19.1