A Mistral-7B-instruct-v0.1 model to extract a title from the text of Italian law articles. It is fine-tuned over a set of 100k text-title pairs that are available throughout the Italian legislation. It can be used to extract titles for articles or attachments that do not have a pre-defined title.

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.

The best model reported an evaluation loss of 1.0030452013015747