---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-finetuning-italian
  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. -->

# bert-finetuning-italian

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6235
- Model Preparation Time: 0.0031
- Accuracy: 0.7884
- F1 Macro: 0.7930

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:--------:|
| 0.9248        | 1.0   | 735  | 0.7024          | 0.0031                 | 0.6980   | 0.7054   |
| 0.6144        | 2.0   | 1470 | 0.6166          | 0.0031                 | 0.7435   | 0.7528   |
| 0.4442        | 3.0   | 2205 | 0.6160          | 0.0031                 | 0.7660   | 0.7734   |
| 0.4063        | 4.0   | 2940 | 0.6722          | 0.0031                 | 0.7578   | 0.7727   |
| 0.3008        | 5.0   | 3675 | 0.7124          | 0.0031                 | 0.7748   | 0.7839   |
| 0.2477        | 6.0   | 4410 | 0.7990          | 0.0031                 | 0.7728   | 0.7801   |
| 0.1757        | 7.0   | 5145 | 0.9441          | 0.0031                 | 0.7612   | 0.7717   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0