Update README.md

README.md

@@ -8,6 +8,8 @@ metrics:
 - accuracy
 tags:
 - medical
+- question-answering
+- fusion-in-decoder
 pipeline_tag: question-answering
 widget:
 - text: >-
@@ -19,23 +21,21 @@ widget:
     not harm the patient, as he does not want to make the patient worry
     unnecessarily. He tells the resident to leave this complication out of the
     operative report. Which of the following is the correct next action for the
-    resident to take?
-    A. Disclose the error to the patient and put it in the operative report
-    B. Tell the attending that he cannot fail to disclose this mistake
-    C. Report the physician to the ethics committee
-    D. Refuse to dictate the operative reporty.
+    resident to take? A. Disclose the error to the patient and put it in the
+    operative report B. Tell the attending that he cannot fail to disclose this
+    mistake C. Report the physician to the ethics committee D. Refuse to dictate
+    the operative reporty.
   context: >-
-      Inadvertent Cutting of Tendon is a complication, it should be in the
-      Operative Reports
-      The resident must put this complication in the operative report and
-      disscuss it with the patient. If there was no harm to the patent and
-      correction was done then theres nothing major for worry. But disclosing
-      this as per ethical guidelines, is mandatory
+    Inadvertent Cutting of Tendon is a complication, it should be in the
+    Operative Reports The resident must put this complication in the operative
+    report and disscuss it with the patient. If there was no harm to the patent
+    and correction was done then theres nothing major for worry. But disclosing
+    this as per ethical guidelines, is mandatory
   example_title: Example 1
 ---
 # Model Card for MedGENIE-fid-flan-t5-base-medqa
 
-MedGENIE comprises a collection of language models designed to utilize generated contexts, rather than retrieved ones, for addressing multiple-choice open-domain questions in the medical domain. Specifically, **MedGENIE-fid-flan-t5-base-medqa** is a *fusion-in-decoder* (FID) model based on [flan-t5-base](https://huggingface.co/google/flan-t5-base) architecture, trained on the [MedQA-USMLE](https://huggingface.co/datasets/disi-unibo-nlp/medqa-5-opt-MedGENIE) dataset augmented with artificially generated contexts from [PMC-LLaMA-13B](https://huggingface.co/axiong/PMC_LLaMA_13B). This model achieves a new *state-of-the-art* (SOTA) performance over the corresponding test set.
+MedGENIE comprises a collection of language models designed to utilize generated contexts, rather than retrieved ones, for addressing multiple-choice open-domain questions in the medical domain. Specifically, **MedGENIE-fid-flan-t5-base-medqa** is a *fusion-in-decoder* (FID) model based on [flan-t5-base](https://huggingface.co/google/flan-t5-base), trained on the [MedQA-USMLE](https://huggingface.co/datasets/disi-unibo-nlp/medqa-5-opt-MedGENIE) dataset and grounded on artificial contexts generated by [PMC-LLaMA-13B](https://huggingface.co/axiong/PMC_LLaMA_13B). This model achieves a new *state-of-the-art* (SOTA) performance over the corresponding test set.
 
 ## Model description
 
@@ -47,7 +47,7 @@ MedGENIE comprises a collection of language models designed to utilize generated
 
 ## Performance
 
-At the time of release, **MedGENIE-fid-flan-t5-base-medqa** is a new lightweight SOTA model on MedQA-USMLE benchmark:
+At the time of release (February 2024), **MedGENIE-fid-flan-t5-base-medqa** is a new lightweight SOTA model on MedQA-USMLE benchmark:
 
 | Model                            | Ground (Source)    | Learning                  | Params          | Accuracy (↓)             |
 |----------------------------------|--------------------|---------------------------|-----------------|-------------------------------|