SEA-LION-BERT is an encoder model using the MosaicBERT architecture.
Parameter
SEA-LION-BERT
Layers
12
d_model
768
head_dim
12
Vocabulary
256000
Sequence Length
128
Tokenizer Details
We sample 20M lines from the training data to train the tokenizer.
The framework for training is
SentencePiece
.
The tokenizer type is Byte-Pair Encoding (BPE).
The Team
Montalan Jann Railey
Nguyen Thanh Ngan
Rengarajan Hamsawardhini
Teo Eng Sipp Leslie
Tjhi William
Acknowledgements
AI Singapore is a national programme supported by the National Research Foundation, Singapore and hosted by the National University of Singapore.
Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore.
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