End of training

README.md

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+---
+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