caiomauro/trader-sentiment

---
license: mit
language:
- en
size_categories:
- n<1K
---

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.

原始信息汇总

数据集概述

基本信息

• 许可证: MIT
• 语言: 英语
• 数据集大小: 小于1000条记录

数据集内容

• 目的: 用于训练一个大型语言模型（LLM），从r/wallstreetbets子论坛中提取股票特定情绪。
• 数据处理: 通过AI快速扫描帖子，分析内容，并确定用户对X、Y、Z股票的情感倾向（正面、负面、混合或中性）。
• 数据存储: 存储在本地SQLite数据库中。
• 数据量: 约450行数据，其中约225行用于训练LLM进行结构化分析，其余用于训练模型将分析结果转换为可解析的字符串。