{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/reactiont5-a-large-scale-pre-trained-model","title":"ReactionT5: a large-scale pre-trained model towards application of limited reaction data","arxiv_id":"2311.06708","date":"2023-11-12","proceeding":null,"authors":["Tatsuya Sagawa","Ryosuke Kojima"],"abstract":"Transformer-based deep neural networks have revolutionized the field of molecular-related prediction tasks by treating molecules as symbolic sequences. These models have been successfully applied in various organic chemical applications by pretraining them with extensive compound libraries and subsequently fine-tuning them with smaller in-house datasets for specific tasks. However, many conventional methods primarily focus on single molecules, with limited exploration of pretraining for reactions involving multiple molecules. In this paper, we propose ReactionT5, a novel model that leverages pretraining on the Open Reaction Database (ORD), a publicly available large-scale resource. We further fine-tune this model for yield prediction and product prediction tasks, demonstrating its impressive performance even with limited fine-tuning data compared to traditional models. The pre-trained ReactionT5 model is publicly accessible on the Hugging Face platform.","url_abs":"https://arxiv.org/abs/2311.06708v1","url_pdf":"https://arxiv.org/pdf/2311.06708v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"reactiont5-a-large-scale-pre-trained-model","repo_url":"https://github.com/sagawatatsuya/ReactionT5","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"jax","reach":null}],"tasks":[{"task_slug":"prediction","task_name":"Prediction"}],"methods":[{"method_slug":"focus","method_name":"Focus"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2311.06708","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}