size_categories:100K<n<1M format:parquet modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
dataset_info:
  config_name: default_123
  features:
  - name: text
    dtype: string
  - name: id
    dtype: string
  - name: dump
    dtype: string
  - name: url
    dtype: string
  - name: date
    dtype: string
  - name: file_path
    dtype: string
  - name: language
    dtype: string
  - name: language_score
    dtype: float64
  - name: token_count
    dtype: int64
  - name: score
    dtype: float64
  - name: int_score
    dtype: int64
  splits:
  - name: train
    num_bytes: 1716261451
    num_examples: 500000
  download_size: 1015330377
  dataset_size: 1716261451
configs:
- config_name: default_123
  data_files:
  - split: train
    path: default_123/train-*
---
the scores (int_score) are inversed , 30 and bellow that means that the text is healthcare related. (95% accuracy according to llama-3-8b-instruct as judge)