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# test_dino-large-2025_05_19_65652-bs16_freeze

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: 0.0573
- F1 Micro: 0.6898
- F1 Macro: 0.1356
- Accuracy: 0.5959
- Learning Rate: 0.0005

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:------:|
| 0.0771        | 1.0   | 1081 | 0.0632          | 0.6761   | 0.1357   | 0.5803   | 0.0005 |
| 0.0671        | 2.0   | 2162 | 0.0594          | 0.6917   | 0.1381   | 0.6018   | 0.0005 |
| 0.0664        | 3.0   | 3243 | 0.0612          | 0.6820   | 0.1381   | 0.6087   | 0.0005 |
| 0.0636        | 4.0   | 4324 | 0.0574          | 0.6980   | 0.1413   | 0.6080   | 0.0005 |
| 0.063         | 5.0   | 5405 | 0.0581          | 0.6880   | 0.1375   | 0.6032   | 0.0005 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.6.0+cu118
- Datasets 3.0.2
- Tokenizers 0.21.1

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