{"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/torchbearer-a-model-fitting-library-for","title":"Torchbearer: A Model Fitting Library for PyTorch","arxiv_id":"1809.03363","date":"2018-09-10","proceeding":null,"authors":["Ethan Harris","Matthew Painter","Jonathon Hare"],"abstract":"We introduce torchbearer, a model fitting library for pytorch aimed at\nresearchers working on deep learning or differentiable programming. The\ntorchbearer library provides a high level metric and callback API that can be\nused for a wide range of applications. We also include a series of built in\ncallbacks that can be used for: model persistence, learning rate decay,\nlogging, data visualization and more. The extensive documentation includes an\nexample library for deep learning and dynamic programming problems and can be\nfound at http://torchbearer.readthedocs.io. The code is licensed under the MIT\nLicense and available at https://github.com/ecs-vlc/torchbearer.","url_abs":"http://arxiv.org/abs/1809.03363v1","url_pdf":"http://arxiv.org/pdf/1809.03363v1.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":"torchbearer-a-model-fitting-library-for","repo_url":"https://github.com/ecs-vlc/torchbearer","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"torchbearer-a-model-fitting-library-for","repo_url":"https://github.com/pytorchbearer/torchbearer","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"data-visualization","task_name":"Data Visualization"},{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}