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# DinoAmoros-small-2025_05_06_34659-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: 3.1588
- F1 Micro: 0.2
- F1 Macro: 0.1339
- 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    | 3.3289          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 2.0   | 2    | 3.2965          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 3.0   | 3    | 3.2832          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 4.0   | 4    | 3.2658          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 5.0   | 5    | 3.2574          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 6.0   | 6    | 3.2430          | 0.1      | 0.0444   | 0.1      | 0.001  |
| No log        | 7.0   | 7    | 3.2252          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 8.0   | 8    | 3.2078          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 9.0   | 9    | 3.2320          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 10.0  | 10   | 3.2318          | 0.0      | 0.0      | 0.0      | 0.001  |
| No log        | 11.0  | 11   | 3.2295          | 0.1      | 0.0417   | 0.1      | 0.001  |
| No log        | 12.0  | 12   | 3.1906          | 0.3      | 0.3254   | 0.3      | 0.001  |
| No log        | 13.0  | 13   | 3.1611          | 0.5      | 0.4278   | 0.5      | 0.001  |
| No log        | 14.0  | 14   | 3.1342          | 0.5      | 0.4278   | 0.5      | 0.001  |
| No log        | 15.0  | 15   | 3.1030          | 0.4      | 0.3333   | 0.4      | 0.001  |
| No log        | 16.0  | 16   | 3.0616          | 0.4      | 0.3333   | 0.4      | 0.001  |
| No log        | 17.0  | 17   | 3.0400          | 0.4      | 0.3333   | 0.4      | 0.001  |
| No log        | 18.0  | 18   | 2.9770          | 0.4      | 0.3810   | 0.4      | 0.001  |
| No log        | 19.0  | 19   | 2.9270          | 0.4      | 0.3810   | 0.4      | 0.001  |
| No log        | 20.0  | 20   | 2.8651          | 0.5      | 0.5      | 0.5      | 0.001  |
| No log        | 21.0  | 21   | 2.8102          | 0.5      | 0.5      | 0.5      | 0.001  |
| No log        | 22.0  | 22   | 2.7777          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 23.0  | 23   | 2.7405          | 0.5      | 0.5      | 0.5      | 0.001  |
| No log        | 24.0  | 24   | 2.6667          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 25.0  | 25   | 2.6132          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 26.0  | 26   | 2.5834          | 0.5      | 0.5      | 0.5      | 0.001  |
| No log        | 27.0  | 27   | 2.5603          | 0.5      | 0.5      | 0.5      | 0.001  |
| No log        | 28.0  | 28   | 2.5502          | 0.5      | 0.5      | 0.5      | 0.001  |
| No log        | 29.0  | 29   | 2.5178          | 0.5      | 0.5      | 0.5      | 0.001  |
| No log        | 30.0  | 30   | 2.4880          | 0.5      | 0.5      | 0.5      | 0.001  |
| No log        | 31.0  | 31   | 2.4448          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 32.0  | 32   | 2.4291          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 33.0  | 33   | 2.4009          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 34.0  | 34   | 2.3793          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 35.0  | 35   | 2.3791          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 36.0  | 36   | 2.3485          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 37.0  | 37   | 2.3341          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 38.0  | 38   | 2.3232          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 39.0  | 39   | 2.3187          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 40.0  | 40   | 2.3267          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 41.0  | 41   | 2.3401          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 42.0  | 42   | 2.3547          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 43.0  | 43   | 2.3599          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 44.0  | 44   | 2.3857          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 45.0  | 45   | 2.4031          | 0.5      | 0.6111   | 0.5      | 0.001  |
| No log        | 46.0  | 46   | 2.3779          | 0.5      | 0.6111   | 0.5      | 0.0001 |
| No log        | 47.0  | 47   | 2.3591          | 0.5      | 0.6111   | 0.5      | 0.0001 |
| No log        | 48.0  | 48   | 2.3669          | 0.5      | 0.6111   | 0.5      | 0.0001 |
| No log        | 49.0  | 49   | 2.3603          | 0.5      | 0.6111   | 0.5      | 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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