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RL ChatMate is an open-source project aimed at improving chatbot interactions using state-of-the-art reinforcement learning techniques. By fine-tuning language models with human feedback, the main goal is to enhance response quality, coherence, and engagement.
The project is organized into the following sections:
README.md: Read about the project and its main goal. About tokenization: a brief description of the tokenization process. Dataset tokenization: Chi-Square Test: The execution of the chi-square test and hypothesis validation.
For this project I will be using the CommonsenseQA dataset.
CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge to predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers. The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation split, and "Question token split", see paper for details.
Originals autors: Alon Talmor, Jonathan Herzig, Nicholas Lourie, Jonathan Berant
From: https://arxiv.org/abs/1811.00937 arXiv:1811.00937v2 [cs.CL]
Official website: