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# prova_riconoscimento

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0
- Accuracy: 1.0

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.89  | 2    | 2.2590          | 0.0      |
| No log        | 1.78  | 4    | 1.8278          | 0.0227   |
| No log        | 2.67  | 6    | 1.2314          | 0.9697   |
| No log        | 4.0   | 9    | 0.4039          | 1.0      |
| 1.5804        | 4.89  | 11   | 0.0799          | 1.0      |
| 1.5804        | 5.78  | 13   | 0.0060          | 1.0      |
| 1.5804        | 6.67  | 15   | 0.0004          | 1.0      |
| 1.5804        | 8.0   | 18   | 0.0000          | 1.0      |
| 0.0314        | 8.89  | 20   | 0.0000          | 1.0      |
| 0.0314        | 9.78  | 22   | 0.0000          | 1.0      |
| 0.0314        | 10.67 | 24   | 0.0000          | 1.0      |
| 0.0314        | 12.0  | 27   | 0.0000          | 1.0      |
| 0.0314        | 12.89 | 29   | 0.0000          | 1.0      |
| 0.0           | 13.78 | 31   | 0.0000          | 1.0      |
| 0.0           | 14.67 | 33   | 0.0000          | 1.0      |
| 0.0           | 16.0  | 36   | 0.0000          | 1.0      |
| 0.0           | 16.89 | 38   | 0.0000          | 1.0      |
| 0.0           | 17.78 | 40   | 0.0000          | 1.0      |
| 0.0           | 18.67 | 42   | 0.0000          | 1.0      |
| 0.0           | 20.0  | 45   | 0.0000          | 1.0      |
| 0.0           | 20.89 | 47   | 0.0000          | 1.0      |
| 0.0           | 21.78 | 49   | 0.0000          | 1.0      |
| 0.0           | 22.67 | 51   | 0.0000          | 1.0      |
| 0.0           | 24.0  | 54   | 0.0             | 1.0      |
| 0.0           | 24.89 | 56   | 0.0             | 1.0      |
| 0.0           | 25.78 | 58   | 0.0             | 1.0      |
| 0.0           | 26.67 | 60   | 0.0             | 1.0      |
| 0.0           | 28.0  | 63   | 0.0             | 1.0      |
| 0.0           | 28.89 | 65   | 0.0             | 1.0      |
| 0.0           | 29.78 | 67   | 0.0             | 1.0      |
| 0.0           | 30.67 | 69   | 0.0             | 1.0      |
| 0.0           | 32.0  | 72   | 0.0             | 1.0      |
| 0.0           | 32.89 | 74   | 0.0             | 1.0      |
| 0.0           | 33.78 | 76   | 0.0             | 1.0      |
| 0.0           | 34.67 | 78   | 0.0             | 1.0      |
| 0.0           | 36.0  | 81   | 0.0             | 1.0      |
| 0.0           | 36.89 | 83   | 0.0             | 1.0      |
| 0.0           | 37.78 | 85   | 0.0             | 1.0      |
| 0.0           | 38.67 | 87   | 0.0             | 1.0      |
| 0.0           | 40.0  | 90   | 0.0             | 1.0      |
| 0.0           | 40.89 | 92   | 0.0             | 1.0      |
| 0.0           | 41.78 | 94   | 0.0             | 1.0      |
| 0.0           | 42.67 | 96   | 0.0             | 1.0      |
| 0.0           | 44.0  | 99   | 0.0             | 1.0      |
| 0.0           | 44.44 | 100  | 0.0             | 1.0      |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

codice_fiscale carta_identita_a carta_identita_b visura_catastale atto_provenienza planimetria