Update README.md

README.md

@@ -14,16 +14,14 @@ tags:
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
-This model create summarizes text paragraphs from medical research journals into brief titles.
-
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+This model is used to automatically generate title from paragraph.
 
 ## Model Details
 
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->
-This is a text generative model to summarize long abstract from medical jourals into one liners. These one liners can be used as titles in the journal.
+This is a text generative model to summarize long abstract text jourals into one liners. These one liners can be used as titles in the journal.
 
 
 - **Developed by:** Tushar Joshi
@@ -42,20 +40,20 @@ This is a text generative model to summarize long abstract from medical jourals
 ## Uses
 
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-* As a text summarizer for medical journals paragraphs
-* As a tunable language model for other medical tasks
-
+* As a text summarizer to create titles.
+* As a tunable language model for downstream tasks.
+  
 ### Direct Use
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-* As a text summarizer for medical abstracts and journals.
+* As a text summarizer for paragraphs.
 
 
 ### Out-of-Scope Use
 
 <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-Should not be used as a text summarizer for very long tasks. Maximum token size of 1024. 
+Should not be used as a text summarizer for very long paragraphs.
 
 ## Bias, Risks, and Limitations
 
@@ -114,7 +112,7 @@ The training was done using GPU T4x 2. The task took 4:09:47 to complete. The da
 ## Evaluation
 
 <!-- This section describes the evaluation protocols and provides the results. -->
-The quality of summarization was tested on 5000 medical journals created over last 20 years. The data of medical jounals is scraped from various sources.
+The quality of summarization was tested on 5000 research journals created over last 20 years.
 
 ### Testing Data, Factors & Metrics