Update README.md

README.md

@@ -12,7 +12,7 @@ probably proofread and complete it, then remove this comment. -->
 
 # Roberta-base-financial-sentiment-analysis
 
-This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
+This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on the financial_phrasebank dataset.
 It achieves the following results on the evaluation set:
 - Train Loss: 0.0030
 - Train Accuracy: 0.9988
@@ -22,15 +22,15 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This is a RoBERTa-base model trained on ~124M tweets from January 2018 to December 2021, and finetuned for sentiment analysis (positive, neutral, negative) with the TweetEval benchmark.
 
 ## Intended uses & limitations
 
-More information needed
+Sentiment analysis for text describing financial markets
 
 ## Training and evaluation data
 
-More information needed
+"The financial_phrasebank dataset contains 4840 sentences describing financial markets in english, with an associated sentiment label as positive, neutral, or negative.
 
 ## Training procedure