---
license: apache-2.0
language:
- it
library_name: peft
pipeline_tag: text-generation
tags:
- legal
base_model: mistralai/Mistral-7B-Instruct-v0.1
---

# Model Description

A Mistral-7B-instruct-v0.1 model to extract the topics from a text of Italian law articles (titles). It is fine-tuned over a set of 74k high quality law title-topics pairs, which were initially obtained from the application of a larger model (Mixtral8x22) and then pre-processed to increase the quality of the training set by means of heuristics that aggregate slighlty different topics and allow the fine-tuned model to achieve an higher diversity


- **Developed by:** Andrea Colombo, Politecnico di Milano
- **Model type:** text generation
- **Language(s) (NLP):** Italian
- **License:** Apache 2.0
- **Finetuned from model:** mistralai/Mistral-7B-Instruct-v0.1


## How to Get Started with the Model


## Training Details

### Training Procedure

The model has been trained for 100 training steps with batch size 4, 4-bit quantization using bitsandbytes and a LoRA rank of 64.
We use the paged Adam optimizer, a learning rate of 0.004, and a cosine learning rate scheduler with a 0.03 warm-up fraction.


## Evaluation

The best model reported an evaluation loss of 0.61