Search results
Results from the WOW.Com Content Network
The original BERT paper published results demonstrating that a small amount of finetuning (for BERT LARGE, 1 hour on 1 Cloud TPU) allowed it to achieved state-of-the-art performance on a number of natural language understanding tasks: [1] GLUE (General Language Understanding Evaluation) task set (consisting of 9 tasks);
The model is prompted to answer a question with an explanation. The model is then prompted to explain parts of the explanation, and so on. Inconsistent explanation trees are pruned or discarded. This improves performance on complex commonsense reasoning. [36] Example: [36] Q: {question} A: True, because Q: {question} A: False, because
a knowledge representation system in the tradition of semantic networks and frames; it is a frame language. MARGIE: 1975 Roger Schank: TaleSpin (software) 1976 Meehan QUALM: Lehnert LIFER/LADDER: 1978 Hendrix a natural language interface to a database of information about US Navy ships. SAM (software) 1978 Cullingford PAM (software) 1978 Robert ...
At the time of the MMLU's release, most existing language models performed around the level of random chance (25%), with the best performing GPT-3 model achieving 43.9% accuracy. [3] The developers of the MMLU estimate that human domain-experts achieve around 89.8% accuracy. [ 3 ]
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
Discover the latest breaking news in the U.S. and around the world — politics, weather, entertainment, lifestyle, finance, sports and much more.
The model was exclusively a foundation model, [6] although the paper contained examples of instruction fine-tuned versions of the model. [ 2 ] Meta AI reported the 13B parameter model performance on most NLP benchmarks exceeded that of the much larger GPT-3 (with 175B parameters), and the largest 65B model was competitive with state of the art ...
The model, as well as the code base and the data used to train it, are distributed under free licences. [3] BLOOM was trained on approximately 366 billion (1.6TB) tokens from March to July 2022. [4] [5] BLOOM is the main outcome of the BigScience collaborative initiative, [6] a one-year-long research workshop that took place between May 2021 ...