MathBERT model (original vocab) Disclaimer: the format of the documentation follows the official BERT model readme.md Pretrained model on pre k to graduate math language (English) using a masked language modeling (MLM) objective. This model is uncased: it does not make a difference between english and English. Model description MathBERT is a transformers model pretrained on a large corpus of English math corpus data in a self supervised fashion. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely, it was pretrained with two objectives: Masked language modeling (MLM): taking a sentence, the model randomly masks 15% of the words in the input then run the entire masked sentence through the model and has to predict the masked words. This is different from traditional recurrent neural networks (RNNs) that usually see the words one after the other, or from autoregressive models like GPT which internally mask the future tokens. It allows the model to learn a bidirectional representation of the sentence.…
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