caiomauro/trader-sentiment
Hello! Welcome to my first dataset! Background: For my first AI project I wrote a fine-tuned a model and trained a LLM to pull stock specific sentiments from the r/wallstreetbets subreddit. My goal was not to make predictions based on the content but to use AI to quickly scan over posts, analyze what is being said, and determine if the user is postive, negative, mixed or nuetral about X,Y and Z stock. The data is then saved in a local sqlite DB and is visualized @… See the full description on the dataset page: https://huggingface.co/datasets/caiomauro/trader-sentiment.
Hello! Welcome to my first dataset!
Background: For my first AI project I wrote a fine-tuned a model and trained a LLM to pull stock specific sentiments from the r/wallstreetbets subreddit. My goal was not to make predictions based on the content but to use AI to quickly scan over posts, analyze what is being said, and determine if the user is postive, negative, mixed or nuetral about X,Y and Z stock. The data is then saved in a local sqlite DB and is visualized @ https://wsb-analytics.vercel.app/ (Django backend is only up sometimes).
This data set includes AI generated input's and output's made using GPT4 through relavance.ai and their batch jobs! This portion is ~450 lines of data where ~225 are to train the LLM to produce a structured analysis and the other half trained the model to take that analysis and then provide a predictable string that could be parsed into an array.