As new AI models and methods are introduced to the market there needed to be an objective way to benchmark them against the current offerings.
GLUE
In 2018 the community introduced the GLUE (General Language Understanding Evaluation benchmark) benchmark. You can readd the full paper here: [1804.07461] GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding (arxiv.org)
The GLUE offered a single-number metric that summarizes progress on a diverse set of tasks, but performance on the benchmark has recently surpassed the level of non-expert humans, suggesting limited headroom for further research.
SuperGLUE
The community realized a need for a more comprehensive way to benchmark models. in 2019 the SuperGLUE was introduced, a new benchmark styled after GLUE with a new set of more difficult language understanding tasks, a software toolkit, and a public leaderboard. SuperGLUE retains the two hardest tasks in GLUE. The remaining tasks were identified from those submitted to an open call for task proposals and were selected based on difficulty for current NLP approaches.
The tasks include:
- BoolQ: Given a short passage and a yes/no question, determine whether the passage contains the answer to the question.
- CB: Given a short passage and a question with a multiple-choice answer, select the correct answer.
- COPA: Given a premise and a question with two possible choices, select the choice that best completes the question.
- MultiRC: Given a passage and a set of questions, select the correct answer to each question, with some questions requiring multiple answers.
- ReCoRD: Given a passage with missing words and a set of possible replacements for each blank, select the correct replacement for each blank.
- RTE: Given two sentences, determine whether the second sentence is entailed by the first.
- WiC: Given a word and two sentences that use the word, determine whether the word has the same meaning in both sentences.
- WSC: Given a sentence with a pronoun and a second sentence, determine whether the pronoun in the first sentence refers to the same entity as a word in the second sentence.
The SuperGLUE process is detailed here: [1905.00537] SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems (arxiv.org)
Model benchmarks is published here SuperGLUE
Final Thoughts
It is important to consider a variety of factors, including the specific task you are trying to accomplish, the size of your dataset, and the computational resources available to you. While SuperGLUE scores can be a useful guide in this process, they are not the only factor to consider.
We recommend that you work closely with our team of experts to determine the best approach for your project, taking into account the specific requirements and constraints that you are working with. Our team has extensive experience in natural language processing and can help you select the best model for your nee
