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# DinoAmoros-small-2025_05_06_35666-prova_bs16_freeze_monolabel

This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7420
- F1 Micro: 0.2
- F1 Macro: 0.0889
- Accuracy: 0.2
- Learning Rate: 0.0001

## 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: 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: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:------:|
| No log        | 1.0   | 1    | 3.1514          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 2.0   | 2    | 3.1508          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 3.0   | 3    | 3.1557          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 4.0   | 4    | 3.1625          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 5.0   | 5    | 3.1223          | 0.2      | 0.0571   | 0.2      | 0.001  |
| No log        | 6.0   | 6    | 3.1340          | 0.1      | 0.04     | 0.1      | 0.001  |
| No log        | 7.0   | 7    | 3.1654          | 0.2      | 0.0606   | 0.2      | 0.001  |
| No log        | 8.0   | 8    | 3.1547          | 0.3      | 0.1667   | 0.3      | 0.001  |
| No log        | 9.0   | 9    | 3.1387          | 0.3      | 0.1667   | 0.3      | 0.001  |
| No log        | 10.0  | 10   | 3.1150          | 0.3      | 0.1481   | 0.3      | 0.001  |
| No log        | 11.0  | 11   | 3.0898          | 0.3      | 0.1667   | 0.3      | 0.001  |
| No log        | 12.0  | 12   | 3.0465          | 0.1      | 0.0444   | 0.1      | 0.001  |
| No log        | 13.0  | 13   | 3.0262          | 0.1      | 0.05     | 0.1      | 0.001  |
| No log        | 14.0  | 14   | 3.0098          | 0.2      | 0.1222   | 0.2      | 0.001  |
| No log        | 15.0  | 15   | 3.0078          | 0.2      | 0.1371   | 0.2      | 0.001  |
| No log        | 16.0  | 16   | 3.0350          | 0.2      | 0.1371   | 0.2      | 0.001  |
| No log        | 17.0  | 17   | 3.0396          | 0.2      | 0.1467   | 0.2      | 0.001  |
| No log        | 18.0  | 18   | 3.0520          | 0.1      | 0.0667   | 0.1      | 0.001  |
| No log        | 19.0  | 19   | 3.0697          | 0.1      | 0.0667   | 0.1      | 0.001  |
| No log        | 20.0  | 20   | 3.1036          | 0.2      | 0.1467   | 0.2      | 0.001  |
| No log        | 21.0  | 21   | 3.1122          | 0.2      | 0.16     | 0.2      | 0.001  |
| No log        | 22.0  | 22   | 3.1102          | 0.1      | 0.08     | 0.1      | 0.0001 |
| No log        | 23.0  | 23   | 3.1098          | 0.2      | 0.16     | 0.2      | 0.0001 |
| No log        | 24.0  | 24   | 3.1053          | 0.2      | 0.1467   | 0.2      | 0.0001 |
| No log        | 25.0  | 25   | 3.0939          | 0.2      | 0.16     | 0.2      | 0.0001 |


### Framework versions

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

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