---
dataset_info:
  features:
  - name: ticker
    dtype: string
  - name: prompt
    dtype: string
  - name: text
    dtype: string
  - name: url
    dtype: string
  - name: result_1
    dtype: string
  - name: result_1_bin
    dtype: int64
  - name: relevance
    dtype: string
  - name: token_count
    dtype: int64
  - name: __index_level_0__
    dtype: int64
  splits:
  - name: train
    num_bytes: 12167785
    num_examples: 3600
  - name: val
    num_bytes: 708256
    num_examples: 200
  - name: test
    num_bytes: 698513
    num_examples: 200
  download_size: 7170454
  dataset_size: 13574554
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: val
    path: data/val-*
  - split: test
    path: data/test-*
---

## INFO

A random selection of news articles and tweets for the purpose of fine-tuning a LLM to predict stock price movement the day after the news publications/tweets.

Source koen430/preprocessed_stock_news and koen430/preprocessed_stock_twitter

More info will follow soon