Update README.md

README.md

@@ -4,4 +4,64 @@ datasets:
 - natural_questions
 language:
 - en
----
+tags:
+- colbert
+---
+# ColBERT NQ Checkpoint
+
+This trained model is based on the [ColBERT](https://github.com/stanford-futuredata/ColBERT) model, trained on the [Natural Questions](https://huggingface.co/datasets/natural_questions) dataset. 
+
+# Model Details
+
+Model is based on ColBERT, which in turn is based around a BERT encoder. The model is trained for text retrieval using a contrastive loss; given a query there's a relevant and non relevant passages. 
+
+The corpus is based on [Wikipeida](https://huggingface.co/datasets/wiki_dpr). 
+
+# Uses
+
+Model can be used by the [ColBERT](https://github.com/stanford-futuredata/ColBERT) codebase to initiate a retriever; one needs to build a vector index and then queries can be ran. 
+
+# Evaluation
+
+Evaluation results on NQ dev:
+
+<table>
+<colgroup>
+<col  class="org-right">
+<col  class="org-right">
+<col  class="org-right">
+</colgroup>
+<thead>
+<tr>
+<th scope="col" class="org-right">NQ</th>
+<th scope="col" class="org-right">Recall</th>
+<th scope="col" class="org-right">MRR</th>
+</tr>
+</thead>
+
+<tbody>
+<tr>
+<td class="org-right">10</td>
+<td class="org-right">71.1</td>
+<td class="org-right">52.0</td>
+</tr>
+
+<tr>
+<td class="org-right">20</td>
+<td class="org-right">76.3</td>
+<td class="org-right">52.3</td>
+</tr>
+
+<tr>
+<td class="org-right">50</td>
+<td class="org-right">80.4</td>
+<td class="org-right">52.5</td>
+</tr>
+
+<tr>
+<td class="org-right">100</td>
+<td class="org-right">82.7</td>
+<td class="org-right">52.5</td>
+</tr>
+</tbody>
+</table>