Lisbon Computational Linguists at SemEval-2024 Task 2: Using a Mistral-7B Model and Data Augmentation
Artur Guimarães, Bruno Martins, João Magalhães · 2024
This paper describes our approach to the SemEval-2024 safe biomedical Natural Language Inference for Clinical Trials (NLI4CT) task, which concerns classifying statements about Clinical Trial Reports (CTRs).We explored the capabilities of Mistral-7B, a generalist open-source Large Language Model (LLM).We developed a prompt for the NLI4CT task, and fine-tuned a quantized version of the model using an augmented version of the training dataset.The experimental results show that this approach can produce notable results in terms of the macro F1-score, while having limitations in terms of faithfulness and consistency.All the developed code is publicly available on a GitHub repository 1 .