Update README.md

README.md

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 # FinTwitBERT-sentiment
 
-FinTwitBERT-sentiment is a finetuned model for classifying the sentiment of financial tweets. It uses [FinTwitBERT](https://huggingface.co/StephanAkkerman/FinTwitBERT) as a base model, which has been pre-trained on 1 million financial tweets.
+FinTwitBERT-sentiment is a finetuned model for classifying the sentiment of financial tweets. It uses [FinTwitBERT](https://huggingface.co/StephanAkkerman/FinTwitBERT) as a base model, which has been pre-trained on 10 million financial tweets.
 This approach ensures that the FinTwitBERT-sentiment has seen enough financial tweets, which have an informal nature, compared to other financial texts, such as news headlines.
 Therefore this model performs great on informal financial texts, seen on social media.
 
@@ -47,6 +47,12 @@ Therefore this model performs great on informal financial texts, seen on social
 
 FinTwitBERT-sentiment is intended for classifying financial tweets or other financial social media texts.
 
+## Dataset
+
+FinTwitBERT-sentiment has been trained on two datasets. One being a collection of several financial tweet datasets and the other a synthetic dataset created out of the first.
+- [TimKoornstra/financial-tweets-sentiment](https://huggingface.co/datasets/TimKoornstra/financial-tweets-sentiment): 38,091 human-labeled tweets
+- [TimKoornstra/synthetic-financial-tweets-sentiment](https://huggingface.co/datasets/TimKoornstra/synthetic-financial-tweets-sentiment): 1,428,771 synethtic tweets
+
 ## More Information
 
 For a comprehensive overview, including the training setup and analysis of the model, visit the [FinTwitBERT GitHub repository](https://github.com/TimKoornstra/FinTwitBERT).