Updated the model readme

README.md

@@ -7,7 +7,7 @@ datasets:
 metrics:
 - accuracy
 model-index:
-- name: my_awesome_model
+- name: neuroapps_sentiment_classifier
   results:
   - task:
       name: Text Classification
@@ -24,10 +24,7 @@ model-index:
       value: 0.93188
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# my_awesome_model
+# neuroapps_sentiment_classifier
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
 It achieves the following results on the evaluation set:
@@ -36,15 +33,15 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This model outputs the sentiment value, either positive or negative from the sentence or phrase.
 
 ## Intended uses & limitations
 
-More information needed
+This model could be used for extracting sentiments from product reviews, product feedback, or general conversational text. 
 
 ## Training and evaluation data
 
-More information needed
+his model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
 
 ## Training procedure