Statements (160)
Predicate | Object |
---|---|
gptkbp:instance_of |
gptkb:software
gptkb:language |
gptkbp:bfsLayer |
3
|
gptkbp:bfsParent |
gptkb:Job_Search_Engine
gptkb:studio |
gptkbp:allows |
May Overfit Small Datasets
Not Always Interpretable Requires Large Compute Resources Sensitive to Input Quality |
gptkbp:application |
natural language understanding
question answering sentiment analysis |
gptkbp:applies_to |
language translation
text summarization text classification |
gptkbp:architectural_style |
gptkb:Transformers_character
|
gptkbp:based_on |
gptkb:Transformer_Architecture
self-attention mechanism encoder-decoder architecture |
gptkbp:community_support |
high
|
gptkbp:developed_by |
gptkb:Job_Search_Engine
|
gptkbp:has_achievements |
gptkb:GLUE_Benchmark
state-of-the-art results S Qu AD Benchmark |
gptkbp:has_method |
110 million
345 million (large model) |
gptkbp:has_programs |
gptkb:Educational_Institution
gptkb:railway_line Finance Healthcare Legal |
gptkbp:has_variants |
gptkb:Distil_BERT
gptkb:Bio_BERT gptkb:Clinical_BERT gptkb:Tiny_BERT gptkb:m_BERT gptkb:BERT-Base gptkb:BERT-Large ALBERT Ro BER Ta BER Tweet XLM-Ro BER Ta |
https://www.w3.org/2000/01/rdf-schema#label |
BERT
|
gptkbp:impact |
gptkb:significant
|
gptkbp:improves |
gptkb:computer
Named Entity Recognition Question Answering question answering sentiment analysis named entity recognition |
gptkbp:influenced_by |
gptkb:GPT
EL Mo |
gptkbp:input_output |
contextual embeddings
512 tokens tokenized text softmax layer |
gptkbp:introduced |
gptkb:2018
|
gptkbp:is_available_in |
gptkb:Graphics_Processing_Unit
gptkb:Hugging_Face_Transformers gptkb:Py_Torch |
gptkbp:is_available_on |
gptkb:Hugging_Face_Transformers
gptkb:Py_Torch_Hub gptkb:Tensor_Flow_Hub |
gptkbp:is_cited_in |
Conferences
Industry Applications Numerous Research Papers Academic Publications over 10000 |
gptkbp:is_evaluated_by |
gptkb:municipality
Accuracy F1 Score Precision Recall F1 score accuracy precision |
gptkbp:is_known_for |
contextual embeddings
bidirectional training transfer learning in NLP |
gptkbp:is_open_source |
gptkb:theorem
|
gptkbp:is_part_of |
NLP Research Community
|
gptkbp:is_popular_in |
gptkb:Research_Institute
industry applications AI development |
gptkbp:is_related_to |
gptkb:Artificial_Intelligence
gptkb:software gptkb:software_framework gptkb:Deep_Learning Text Mining Semantic Analysis |
gptkbp:is_scalable |
Multiple Languages
Large Datasets Domain-Specific Tasks |
gptkbp:is_tasked_with |
natural language processing
|
gptkbp:is_used_in |
gptkb:musician
gptkb:Job_Search_Engine gptkb:academic_research Language Translation Sentiment Analysis Text Summarization chatbots virtual assistants social media analysis customer support systems content recommendation systems |
gptkbp:language |
gptkb:French
gptkb:Spanish gptkb:Native_American_tribe Chinese English Word Piece |
gptkbp:performance |
gptkb:GLUE
gptkb:Co_NLL-2003 gptkb:MNLI gptkb:RACE state-of-the-art S Qu AD |
gptkbp:provides_information_on |
gptkb:Wikipedia
gptkb:Book_Corpus |
gptkbp:publishes |
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
|
gptkbp:related_model |
Base (110 M parameters)
Large (345 M parameters) |
gptkbp:related_to |
gptkb:NLP
deep learning transfer learning contextual embeddings semantic understanding |
gptkbp:release_date |
gptkb:2018
|
gptkbp:successor |
gptkb:Distil_BERT
gptkb:Tiny_BERT ALBERT Ro BER Ta |
gptkbp:supports |
gptkb:streaming_service
fine-tuning |
gptkbp:system_requirements |
TP Us
GP Us |
gptkbp:training |
gptkb:Wikipedia
gptkb:Book_Corpus supervised learning unsupervised learning Masked Language Model Next Sentence Prediction large text corpora days to weeks diverse datasets masked language modeling next sentence prediction |
gptkbp:tuning |
gptkb:Adam_optimizer
gradient descent task-specific datasets |
gptkbp:user_base |
gptkb:physicist
gptkb:software data scientists |
gptkbp:uses |
Attention Mechanism
deep learning attention mechanism masked language modeling Bidirectional Context Word Piece Tokenization next sentence prediction |