Update README.md

README.md

@@ -14,9 +14,14 @@ datasets:
 
 This is the pretrained model presented in [SecBERT: A Pretrained Language Model for Cyber Security Text](https://github.com/jackaduma/SecBERT/), which is a BERT model trained on cyber security text.
 
-The training corpus was papers taken from [APTnotes](https://github.com/kbandla/APTnotes), [Stucco-Data: Cyber security data sources](https://stucco.github.io/data/), [CASIE: Extracting Cybersecurity Event Information from Text](https://ebiquity.umbc.edu/_file_directory_/papers/943.pdf), [SemEval-2018 Task 8: Semantic Extraction from CybersecUrity REports using Natural Language Processing (SecureNLP)](https://competitions.codalab.org/competitions/17262). 
-
-SecBERT has its own wordpiece vocabulary (secvocab) that's built to best match the training corpus. We trained [BERT](https://huggingface.co/jackaduma/SecBERT) and [SecRoBERTa](https://huggingface.co/jackaduma/SecRoBERTa) versions. 
+The training corpus was papers taken from 
+ * [APTnotes](https://github.com/kbandla/APTnotes)
+ * [Stucco-Data: Cyber security data sources](https://stucco.github.io/data/)
+ * [CASIE: Extracting Cybersecurity Event Information from Text](https://ebiquity.umbc.edu/_file_directory_/papers/943.pdf)
+ * [SemEval-2018 Task 8: Semantic Extraction from CybersecUrity REports using Natural Language Processing (SecureNLP)](https://competitions.codalab.org/competitions/17262). 
+
+SecBERT has its own wordpiece vocabulary (secvocab) that's built to best match the training corpus. We trained [BERT](https://huggingface.co/jackaduma/SecBERT) and 
+[SecRoBERTa](https://huggingface.co/jackaduma/SecRoBERTa) versions. 
 
 Available models include:
 * `SecBERT`