---
license: apache-2.0
task_categories:
- text-classification
- question-answering
language:
- it
tags:
  - italian
  - embeddings
  - bert
  - fine-tuning
  - information-retrieval
  - semantic-search
  - natural-language-processing
  - dense-retrieval
  - c4-dataset
pretty_name: Fine-Tuned BERT for Italian Embeddings
size_categories:
- 10M<n<100M
---
# Italian-BERT-FineTuning-Embeddings

This repository contains a comprehensive dataset designed for fine-tuning BERT-based Italian embedding models. The dataset aims to enhance performance on tasks such as **information retrieval**, **semantic search**, and **embeddings generation**.

---

## Dataset Overview

This dataset leverages the **C4 dataset** (Italian subset) and employs advanced techniques like **sliding window segmentation** and **in-document sampling** to create high-quality, diverse examples from large Italian documents.

### Data Format

The dataset is stored in `.jsonl` format with the following fields:
- `query`: A query or sentence fragment.
- `positive`: A relevant text segment closely associated with the query.
- `hard_negative`: A challenging non-relevant text segment, similar in context but unrelated to the query.

#### Example:
```json
{
  "query": "Stanchi di non riuscire a trovare il partner perfetto?.",
  "positive": "La cosa principale da fare è pubblicare il proprio annuncio e aspettare una risposta.",
  "hard_negative": "Quale rapporto tra investimenti IT e sicurezza?"
}
```
---

### Dataset Statistics

- **Training Set**: 1.13 million rows (~4.5 GB)
- **Test Set**: 9.09 million rows (~0.5 GB)

---

### Dataset Construction

This dataset was built using the following methodologies:

1. **Sliding Window Segmentation**  
   Extracting overlapping text segments to preserve contextual information and maximize coverage of the source material.

2. **In-Document Sampling**  
   Sampling relevant (`positive`) and challenging non-relevant (`hard_negative`) examples within the same document to ensure robust and meaningful examples.

**Why C4?**  
The C4 dataset was selected due to its vast collection of high-quality Italian text, providing a rich source for creating varied training samples.

---

## Fine-Tuned Model

A fine-tuned BERT-based Italian embedding model trained on this dataset is available:  
**[Fine-Tuned Model Repository](<will-be-added>)**

### Model Base:
- **[dbmdz/bert-base-italian-xxl-uncased](<https://huggingface.co/dbmdz/bert-base-italian-xxl-uncased>)**

---

## Licensing and Usage

This dataset is licensed under the **Apache 2.0 License**. If you use this dataset or the fine-tuned model in your research or applications, please provide appropriate credit:

> **Archit Rastogi**  
> Email: [architrastogi20@gmail.com](mailto:architrastogi20@gmail.com)

---

## Contact

For any questions, feedback, or collaboration inquiries, feel free to reach out:

**Archit Rastogi**  
Email: [architrastogi20@gmail.com](mailto:architrastogi20@gmail.com)

---

Feel free to suggest improvements. Your feedback is highly appreciated!