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README.md

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 SEC-BERT is a family of BERT models for the financial domain, intended to assist financial NLP research and FinTech applications.
 SEC-BERT consists of the following models:
-* [SEC-BERT-BASE](https://huggingface.co/nlpaueb/sec-bert-base)
-* [SEC-BERT-NUM](https://huggingface.co/nlpaueb/sec-bert-num) : We replace every number token with a [NUM] pseudo-token handling all numeric expressions in a uniform manner, disallowing their fragmentation)
-* SEC-BERT-SHAPE (this model): We replace numbers with pseudo-tokens that represent the number’s shape, so numeric expressions (of known shapes) are no longer fragmented.<br>
+* [SEC-BERT-BASE](https://huggingface.co/nlpaueb/sec-bert-base): Same architecture as BERT-BASE trained on financial documents.
+* [SEC-BERT-NUM](https://huggingface.co/nlpaueb/sec-bert-num): Same as SEC-BERT-BASE but we replace every number token with a [NUM] pseudo-token handling all numeric expressions in a uniform manner, disallowing their fragmentation)
+* SEC-BERT-SHAPE (this model): Same as SEC-BERT-BASE but we replace numbers with pseudo-tokens that represent the number’s shape, so numeric expressions (of known shapes) are no longer fragmented.<br>
 (e.g. , '53.2' becomes '[XX.X]' and '40,200.5' becomes '[XX,XXX.X]').<br>
 
 ## Pre-training corpus