Update README.md

README.md

@@ -18,10 +18,77 @@ Use https://github.com/nlmatics/nlm-utils
 
 Click on each model to see details:
 
-1. [roberta.large.boolq](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.boolq)   
-2. [roberta.large.qa](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.qa)
-3. [roberta.large.stsb](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.stsb)
-4. [roberta.large.phraseqa](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.phraseqa)
-5. [roberta.large.qasrl](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.qasrl)
-6. [roberta.large.qatype.lower.RothWithQ](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.qatype.lower.RothWithQ)
-7. [roberta.large.io_qa](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.io_qa)
+### roberta.large.boolq
+
+Location: [roberta.large.boolq](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.boolq)  
+
+Trained with MNLI + Boolq
+
+Trained by: Evan Li
+
+Application: Given a passage and a question, answer the question with yes, no or unsure.
+
+Training Process: https://blogs.nlmatics.com/2020/03/12/Boolean-Question-Answering-with-Neutral-Labels.html
+
+### roberta.large.qa
+See folder: [roberta.large.qa](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.qa)  
+
+Trained with SQuAD 2.0 + Custom Dataset preferring shorter spans better suited for data extraction
+
+Trained by: Ambika Sukla
+
+Application: Given a passage and a question, pick the shortest span from the passage that answers the question
+
+Training Process: start, end location head on the top of Roberta Base
+
+### roberta.large.stsb
+See folder: [roberta.large.stsb](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.stsb)
+
+Trained with STSB dataset
+
+Trained by: Meta/Fairseq
+
+Application: Given two passages, return a score beteen 0 and 1 to evaluate their similarity
+
+Training Process: regression head on top of Roberta Base
+
+### roberta.large.phraseqa
+See folder: [roberta.large.phraseqa](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.phraseqa)
+
+Trained with Roberta 2.0 with the question words removed from the question
+
+Trained By: Batya Stein
+
+Application: Given a passage and phrase (key), extract a value from the passage 
+
+Training Process: https://blogs.nlmatics.com/2020/08/25/Optimizing-Transformer-Q&A-Models-for-Naturalistic-Search.html
+
+### roberta.large.qasrl
+
+See folder: [roberta.large.qasrl](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.qasrl)
+
+Trained with QASRL dataset
+
+Application: Given a passage, get back values for who, what, when, where etc.
+
+Trained By: Nima Sheikholeslami
+
+### roberta.large.qatype.lower.RothWithQ
+
+See folder: [roberta.large.qatype.lower.RothWithQ](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.qatype.lower.RothWithQ)
+
+Trained with the Roth Question Type dataset.
+
+Application: Given a question, return one of the answer types e.g. number, location. See the Roth dataset for full list. 
+
+Trained By: Evan Li
+
+### roberta.large.io_qa
+
+See folder: [roberta.large.io_qa](https://huggingface.co/ansukla/roberta/tree/main/roberta.large.io_qa)
+Trained with SQuAD 2.0 dataset
+
+Trained By: Nima Sheikholeslami
+
+Training Process: Use io head to support multiple spans.
+