Morality is Non-Binary: Building a Pluralist Moral Sentence Embedding Space using Contrastive Learning - models

We train embedding spaces with the MFTC corpus, to see how an embedding space can learn the distribution of pluralist morality. We compare off-the-shelf, unsupervised, and supervised approaches, showing that a supervised approach is necessary. Here, you can find the models we trained with unsupervised and supervised approaches.

我们基于MFTC语料库训练嵌入空间（embedding space），以探究嵌入空间如何学习多元主义道德的分布规律。我们对现成方法、无监督方法与监督方法开展对比实验，结果表明监督方法为不可或缺的训练手段。您可在此处找到我们采用无监督与监督方法训练得到的模型。