This technical report describes the development of WangchanLion, an
instruction fine-tuned model focusing on Machine Reading Comprehension (MRC) in
the Thai language. Our model is based on SEA-LION and a collection of
instruction following datasets. To promote open research and reproducibility,
we publically release all training data, code, and the final model weights
under the Apache-2 license. To assess the contextual understanding capability,
we conducted extensive experimental studies using two Thai MRC datasets, XQuAD
and Iapp_wiki_qa_squad. Experimental results demonstrate the model's ability to
comprehend the context and produce an answer faithful to the reference one in
0-shot and 1-shot settings. In addition, our evaluation goes beyond the
traditional MRC. We propose a new evaluation scheme assessing the answer's
correctness, helpfulness, conciseness, and contextuality. Evaluation results
provide insight into how we can improve our model in the future. Our code is
public at this https URL

该研究报告描述了 WangchanLion 的开发，它是一种针对泰语机器阅读理解（MRC）的指令微调模型。通过使用泰语 MRC 数据集进行广泛的实验研究，我们证明了该模型在零次训练和一次训练设置下，能够理解上下文并生成与参考答案一致的回答。此外，我们还提出了一种新的评估方案，评估答案的正确性、帮助性、简洁性和上下文相关性，评估结果为未来改进模型提供了见解。