Update README.md

README.md

@@ -9,14 +9,13 @@ metrics:
 model-index:
 - name: bertweet-base-finetuned-SARC-combined-DS
   results: []
+widgets:
+- text: wow, i mean who would have thought
 ---
 
-<!-- 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. -->
-
 # bertweet-base-finetuned-SARC-combined-DS
 
-This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the None dataset.
+This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on our combined sarcasm dataset.
 It achieves the following results on the evaluation set:
 - Loss: 1.4624
 - Accuracy: 0.7611
@@ -26,15 +25,13 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
+The given description for BERTweet by VinAI is as follows: <br>
+BERTweet is the first public large-scale language model pre-trained for English Tweets. BERTweet is trained based on the RoBERTa pre-training procedure. The corpus used to pre-train BERTweet consists of 850M English Tweets (16B word tokens ~ 80GB), containing 845M Tweets streamed from 01/2012 to 08/2019 and 5M Tweets related to the COVID-19 pandemic.
+<br>
 
 ## Training and evaluation data
 
-More information needed
+More information neededThis [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) model was finetuned on our combined sarcasm dataset. This dataset was created to aid the building of sarcasm detection models
 
 ## Training procedure