| --- |
| license: apache-2.0 |
| base_model: distilbert/distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: codice_fiscale |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # codice_fiscale |
| |
| This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2024 |
| - Precision: 0.8316 |
| - Recall: 0.5374 |
| - F1: 0.6529 |
| - Accuracy: 0.9405 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 4 | 1.0541 | 0.0 | 0.0 | 0.0 | 0.8445 | |
| | No log | 2.0 | 8 | 0.6374 | 0.0 | 0.0 | 0.0 | 0.8445 | |
| | No log | 3.0 | 12 | 0.5150 | 0.0 | 0.0 | 0.0 | 0.8445 | |
| | No log | 4.0 | 16 | 0.4235 | 0.0 | 0.0 | 0.0 | 0.8445 | |
| | No log | 5.0 | 20 | 0.3564 | 0.5 | 0.0850 | 0.1453 | 0.8667 | |
| | No log | 6.0 | 24 | 0.3024 | 0.5 | 0.0850 | 0.1453 | 0.8667 | |
| | No log | 7.0 | 28 | 0.2609 | 0.6835 | 0.1837 | 0.2895 | 0.8796 | |
| | No log | 8.0 | 32 | 0.2299 | 0.8264 | 0.4048 | 0.5434 | 0.9085 | |
| | No log | 9.0 | 36 | 0.2104 | 0.7826 | 0.4898 | 0.6025 | 0.9280 | |
| | No log | 10.0 | 40 | 0.2024 | 0.8316 | 0.5374 | 0.6529 | 0.9405 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
| |
